{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "from torch import nn\n",
    "from torch import optim\n",
    "from torch.autograd import Variable\n",
    "import sys\n",
    "gpu_id=0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Main code for Concrete Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "class ConcreteDropout(nn.Module):\n",
    "    \"\"\"This module allows to learn the dropout probability for any given input layer.\n",
    "    ```python\n",
    "        # as the first layer in a model\n",
    "        model = nn.Sequential(ConcreteDropout(Linear_relu(1, nb_features),\n",
    "        input_shape=(batch_size, 1), weight_regularizer=1e-6, dropout_regularizer=1e-5))\n",
    "    ```\n",
    "    `ConcreteDropout` can be used with arbitrary layers, not just `Dense`,\n",
    "    for instance with a `Conv2D` layer:\n",
    "    ```python\n",
    "        model = nn.Sequential(ConcreteDropout(Conv2D_relu(channels_in, channels_out),\n",
    "        input_shape=(batch_size, 3, 128, 128), weight_regularizer=1e-6,\n",
    "        dropout_regularizer=1e-5))\n",
    "    ```\n",
    "    # Arguments\n",
    "        layer: a layer Module.\n",
    "        weight_regularizer:\n",
    "            A positive number which satisfies\n",
    "                $weight_regularizer = l**2 / (\\tau * N)$\n",
    "            with prior lengthscale l, model precision $\\tau$ (inverse observation noise),\n",
    "            and N the number of instances in the dataset.\n",
    "            Note that kernel_regularizer is not needed.\n",
    "        dropout_regularizer:\n",
    "            A positive number which satisfies\n",
    "                $dropout_regularizer = 2 / (\\tau * N)$\n",
    "            with model precision $\\tau$ (inverse observation noise) and N the number of\n",
    "            instances in the dataset.\n",
    "            Note the relation between dropout_regularizer and weight_regularizer:\n",
    "                $weight_regularizer / dropout_regularizer = l**2 / 2$\n",
    "            with prior lengthscale l. Note also that the factor of two should be\n",
    "            ignored for cross-entropy loss, and used only for the eculedian loss.\n",
    "    \"\"\"\n",
    "    def __init__(self, layer, input_shape, weight_regularizer=1e-6,\n",
    "                 dropout_regularizer=1e-5, init_min=0.1, init_max=0.1):\n",
    "        super(ConcreteDropout, self).__init__()\n",
    "        # Post drop out layer\n",
    "        self.layer = layer\n",
    "        # Input dim for regularisation scaling\n",
    "        self.input_dim = np.prod(input_shape[1:])\n",
    "        # Regularisation hyper-parameters\n",
    "        self.weight_regularizer = weight_regularizer\n",
    "        self.dropout_regularizer = dropout_regularizer\n",
    "        # Initialise p_logit\n",
    "        init_min = np.log(init_min) - np.log(1. - init_min)\n",
    "        init_max = np.log(init_max) - np.log(1. - init_max)\n",
    "        self.p_logit = nn.Parameter(torch.Tensor(1))\n",
    "        nn.init.uniform(self.p_logit, a=init_min, b=init_max)\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.layer(self._concrete_dropout(x))\n",
    "\n",
    "    def regularisation(self):\n",
    "        \"\"\"Computes weights and dropout regularisation for the layer, has to be\n",
    "        extracted for each layer within the model and added to the total loss\n",
    "        \"\"\"\n",
    "        weights_regularizer = self.weight_regularizer * self.sum_n_square() / (1 - self.p)\n",
    "        dropout_regularizer = self.p * torch.log(self.p)\n",
    "        dropout_regularizer += (1. - self.p) * torch.log(1. - self.p)\n",
    "        dropout_regularizer *= self.dropout_regularizer * self.input_dim\n",
    "        regularizer = weights_regularizer + dropout_regularizer\n",
    "        return regularizer\n",
    "\n",
    "    def _concrete_dropout(self, x):\n",
    "        \"\"\"Forward pass for dropout layer\n",
    "        \"\"\"\n",
    "        eps = 1e-7\n",
    "        temp = 0.1\n",
    "        self.p = nn.functional.sigmoid(self.p_logit)\n",
    "\n",
    "        # Check if batch size is the same as unif_noise, if not take care\n",
    "        unif_noise = Variable(torch.FloatTensor(np.random.uniform(size=tuple(x.size())))).cuda(gpu_id)\n",
    "\n",
    "        drop_prob = (torch.log(self.p + eps)\n",
    "                    - torch.log(1 - self.p + eps)\n",
    "                    + torch.log(unif_noise + eps)\n",
    "                    - torch.log(1 - unif_noise + eps))\n",
    "        drop_prob = nn.functional.sigmoid(drop_prob / temp)\n",
    "        random_tensor = 1 - drop_prob\n",
    "        retain_prob = 1 - self.p\n",
    "        x  = torch.mul(x, random_tensor)\n",
    "        x /= retain_prob\n",
    "        return x\n",
    "\n",
    "    def sum_n_square(self):\n",
    "        \"\"\"Helper function for paramater regularisation\n",
    "        \"\"\"\n",
    "        sum_of_square = 0\n",
    "        for param in self.layer.parameters():\n",
    "            sum_of_square += torch.sum(torch.pow(param, 2))\n",
    "        return sum_of_square\n",
    "    \n",
    "class Linear_relu(nn.Module):\n",
    "    \n",
    "    def __init__(self, inp, out):\n",
    "        super(Linear_relu, self).__init__()\n",
    "        self.model = nn.Sequential(nn.Linear(inp, out), nn.ReLU())\n",
    "        \n",
    "    def forward(self, x):\n",
    "        return self.model(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "class Model(nn.Module):\n",
    "    \"\"\"Below we define the whole model used in the experiment, which\n",
    "    consists of three main layers, and two outputlayers for mean and\n",
    "    log variance\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, wr, dr):\n",
    "        super(Model, self).__init__()\n",
    "        self.forward_main = nn.Sequential(ConcreteDropout(Linear_relu(1, nb_features), input_shape=(batch_size,1), weight_regularizer=wr, dropout_regularizer=dr),\n",
    "                                         ConcreteDropout(Linear_relu(nb_features, nb_features), \n",
    "                                                         input_shape=(batch_size,nb_features), weight_regularizer=wr, dropout_regularizer=dr),\n",
    "                                         ConcreteDropout(Linear_relu(nb_features, nb_features), \n",
    "                                                         input_shape=(batch_size,nb_features), weight_regularizer=wr, dropout_regularizer=dr))\n",
    "        self.forward_mean = ConcreteDropout(Linear_relu(nb_features, D), \n",
    "                                            input_shape=(batch_size,nb_features), weight_regularizer=wr, dropout_regularizer=dr)\n",
    "        self.forward_logvar = ConcreteDropout(Linear_relu(nb_features, D), \n",
    "                                              input_shape=(batch_size,nb_features), weight_regularizer=wr, dropout_regularizer=dr)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = self.forward_main(x)\n",
    "        mean = self.forward_mean(x)\n",
    "        log_var = self.forward_logvar(x)\n",
    "        return mean, log_var\n",
    "\n",
    "    def heteroscedastic_loss(self, true, mean, log_var):\n",
    "        precision = torch.exp(-log_var)\n",
    "        return torch.sum(precision * (true - mean)**2 + log_var)\n",
    "    \n",
    "    def regularisation_loss(self):\n",
    "        reg_loss = self.forward_main[0].regularisation()+self.forward_main[1].regularisation()+self.forward_main[2].regularisation()\n",
    "        reg_loss += self.forward_mean.regularisation()\n",
    "        reg_loss += self.forward_logvar.regularisation()\n",
    "        return reg_loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Set up experiment "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "Ns = [10, 25, 50, 100, 1000, 10000] # Number of data points\n",
    "Ns = np.array(Ns)\n",
    "nb_epochs = [2000, 1000, 500, 200, 20, 2]\n",
    "nb_val_size = 1000 # Validation size\n",
    "nb_features = 1024 # Hidden layer size\n",
    "Q = 1 # Data dimensionality\n",
    "D = 1 # One mean, one log_var\n",
    "K_test = 20 # Number of MC samples\n",
    "nb_reps = 3 # Number of times to repeat experiment\n",
    "batch_size = 20\n",
    "l = 1e-4 # Lengthscale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_data(N):\n",
    "    \"\"\"\n",
    "    Function to generate data\n",
    "    \"\"\"\n",
    "    sigma = 1e0  # ground truth\n",
    "    X = np.random.randn(N, Q)\n",
    "    w = 2.\n",
    "    b = 8.\n",
    "    Y = X.dot(w) + b + sigma * np.random.randn(N, D)\n",
    "    return X, Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "output_type": "display_data"
    },
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac4226c898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pylab\n",
    "%matplotlib inline\n",
    "\n",
    "X, Y = gen_data(10)\n",
    "pylab.figure(figsize=(3, 1.5))\n",
    "pylab.scatter(X[:, 0], Y[:, 0], edgecolor='b')\n",
    "# pylab.savefig('data_10.pdf', bbox_inches='tight')\n",
    "pylab.show()\n",
    "\n",
    "X, Y = gen_data(10000)\n",
    "pylab.figure(figsize=(3, 1.5))\n",
    "pylab.scatter(X[:, 0], Y[:, 0], edgecolor='b')\n",
    "pylab.xlim([-5, 5])\n",
    "pylab.ylim([-2, 20])\n",
    "# pylab.savefig('data_10000.pdf', bbox_inches='tight')\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define fit and evaluation functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_model(nb_epoch, X, Y):\n",
    "    N = X.shape[0]\n",
    "    wr = l**2. / N\n",
    "    dr = 2. / N\n",
    "    model = Model(wr, dr)\n",
    "    model = model.cuda(gpu_id)\n",
    "    optimizer = optim.Adam(model.parameters())\n",
    "    \n",
    "    for i in range(nb_epoch):\n",
    "        old_batch = 0\n",
    "        for batch in range(int(np.ceil(X.shape[0]/batch_size))):\n",
    "            batch = (batch + 1)\n",
    "            _x = X[old_batch: batch_size*batch]\n",
    "            _y = Y[old_batch: batch_size*batch]\n",
    "            \n",
    "            x = Variable(torch.FloatTensor(_x)).cuda(gpu_id)\n",
    "            y = Variable(torch.FloatTensor(_y)).cuda(gpu_id)\n",
    "            \n",
    "            mean, log_var = model(x)\n",
    "            \n",
    "            loss = model.heteroscedastic_loss(y, mean, log_var) + model.regularisation_loss()\n",
    "            \n",
    "            optimizer.zero_grad()\n",
    "            loss.backward()\n",
    "            optimizer.step()\n",
    "            \n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def logsumexp(a):\n",
    "    a_max = a.max(axis=0)\n",
    "    return np.log(np.sum(np.exp(a - a_max), axis=0)) + a_max\n",
    "\n",
    "def test(Y_true, K_test, means, logvar):\n",
    "    \"\"\"\n",
    "    Estimate predictive log likelihood:\n",
    "    log p(y|x, D) = log int p(y|x, w) p(w|D) dw\n",
    "                 ~= log int p(y|x, w) q(w) dw\n",
    "                 ~= log 1/K sum p(y|x, w_k) with w_k sim q(w)\n",
    "                  = LogSumExp log p(y|x, w_k) - log K\n",
    "    :Y_true: a 2D array of size N x dim\n",
    "    :MC_samples: a 3D array of size samples K x N x 2*D\n",
    "    \"\"\"\n",
    "    k = K_test\n",
    "    N = Y_true.shape[0]\n",
    "    mean = means \n",
    "    logvar = logvar\n",
    "    test_ll = -0.5 * np.exp(-logvar) * (mean - Y_val.squeeze())**2. - 0.5 * logvar - 0.5 * np.log(2 * np.pi) #Y_true[None]\n",
    "    test_ll = np.sum(np.sum(test_ll, -1), -1)\n",
    "    test_ll = logsumexp(test_ll) - np.log(k)\n",
    "    pppp = test_ll / N  # per point predictive probability\n",
    "    rmse = np.mean((np.mean(mean, 0) - Y_val.squeeze())**2.)**0.5\n",
    "    return pppp, rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(X_train, Y_train, X_val, Y_val, means):\n",
    "    indx = np.argsort(X_val[:, 0])\n",
    "    _, (ax1, ax2, ax3, ax4) = pylab.subplots(1, 4,figsize=(12, 1.5), sharex=True, sharey=True)\n",
    "    ax1.scatter(X_train[:, 0], Y_train[:, 0], c='y')\n",
    "    ax1.set_title('Train set')\n",
    "    ax2.plot(X_val[indx, 0], np.mean(means, 0)[indx], color='skyblue', lw=3)\n",
    "    ax2.scatter(X_train[:, 0], Y_train[:, 0], c='y')\n",
    "    ax2.set_title('+Predictive mean')\n",
    "    for mean in means:\n",
    "        ax3.scatter(X_val[:, 0], mean, c='b', alpha=0.2, lw=0)\n",
    "    ax3.plot(X_val[indx, 0], np.mean(means, 0)[indx], color='skyblue', lw=3)\n",
    "    ax3.set_title('+MC samples on validation X')\n",
    "    ax4.scatter(X_val[:, 0], Y_val[:, 0], c='r', alpha=0.2, lw=0)\n",
    "    ax4.set_title('Validation set')\n",
    "    pylab.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run the experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41e17588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ca04e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RVcZLAFwJtp0eAF8Di3iAG0YbrfL9dhK/WxbICngWBEEQhLJBPCnQbUopmU1LEIQZRTzDgiAIgiAIwrxFxLAgCIIgCIIwb5EwCUEQBEEQBGHeMq5nmIiWEufS223lmrveWt5APB3fPuu9fvqLKwiCIAiCIAhTx7ieYSJqAdCilHqWiGrAU/y+EZzQfVAp9VUiugFAvVLqk8WO1dTUpFasWDElBRfmJ88880y/UqrYRA3TgtiucLyUw3bFboWpQGxXqEQmYrfjTrph5XTstj6HiWg3eDaTN4CnBgQ4/95D4PRGBVmxYgWefjpvth9BKAkiKjZz2rQhtiscL+WwXbFbYSoQ2xUqkYnY7YQG0BHRCgCnAHgSQLMllLVgXlhgn2uJ6GkievrIkSMT+TlBKCtiu0IlInYrVCpiu0K5KFkME1EAPE3gR5VSI6Xup5S6RSl1qlLq1AULZrx3WxAmjdiuUImI3c4PQiGgu5vf5wpiu0K5GDdMAgCsaf3uAnC7UkrPltJLRC1KqW4rrrhvugopCIIgCAKzfz8wPGy+19UBq1eXrzyCUOmUkk2CwNPr7VZK/T/bqt+BpxuG9X731BdPEARBEARNKDRWCAP8fS55iAVhpinFM/xqAFcDeJGItlvLPgWeL/1OInofgHbwHOqCIAhCBREKAdEo4PcDwWC5SyOMRzRaeLlcP0GYHKVkk3gUABVYfeHUFkcQBEGYKaS7vfLw+0tfLg0dQSiNkmKGBUEQhLlFse52EU6zl2CQGy25jRj7NQuFgF27gGQSCATMNtLQEYT8iBgWBEGYh0h3e2Vh9/KuXl3Y67t/P9DZCXR08PeaGqC1VRo6glAMEcOCIAjzkIl0twszTygE9PTw51gMyGTMOruXVzdqgkGgvR1oawMiEbNtOMzfAwFp6AhCIUQMC4IgzENK6W4XysP+/cCOHSxko1F+X7OGPbwAX7Pt28cK5FAISKWAI0fMPs3NvC4eZzEsDR1ByI+IYUEQhHlKse52oTyEQhzm0NvLMb+xGIvZ3l5urAQC7OmNx4GmJt4nEgG6uoD6ev7u9xsh7fcDPl/+uGK57oLAiBgWBEGYxwSDIoZmE9EocOAAi1+ARW80ykJXe3jjcSCdBvr7WejG47yty8UxwtornM3ytV25Eli2zPyGZBERhLGIGBYEQRCwYwdP7xsIACtWiMewHGiv8MiIWebzAUNDwOAgC2AASCQ4njiZBDwekzHC52NvcSTCgtrv5/UHD3IIhe4JkCwigjAWEcOCIAjznNtuA3bv5njTdJo9ia95jXgMp4NiWSCGh43ojUYBhwPo62OPb1MTv0ejgFImDALgz+vWGVEMsGB2u/maAnzspibJIiII+RAxLAiCMI95/HHg4Ye5qz0W42W7dwPr1xtPooikqUGnPYvH2Yvb2mrOsV6eTnOIQzzOHl6/n0VuXR2L2Zdf5vCI5mYWsNo7vG4dsGgRL9uzxwhqPWguHGZv8qJF+csmg+uE+YyIYUEQhHnK/v3Atm3cDT8ywl3pNTUssHbsMIJLxPDEyfUAh0ImQ4RGe2t37TJ5gQcGOEUaEccJ+/38ymZNyrRk0izX38NhbsD09/P1HBridX6/ySoBmCwiuaJcrrEwnxExLAiCMA/RsaMuFwuwRILFsI5XXbuWBVowCLS0lLeslUa+AWqDg3w+MxnA6WRvLgC89BKL2WgUePFFYHSUvbpKcZjDypVG9MbjQGMjv2ezPMhOC+7RUZNurbGRl0Wj5tXcXNgrLAhlZyLpTaYhFYqIYUEQhHlINMrewZ4eFm6pFL+UAqqrWVwdOcLiSkIlSid3gFokArzwAjc29u833tiGBq7Lly/n7Ts62COcTnMDpb6er1FvLwtZnSItGGQh3dEBeL18zRwOk25N79/SwtcvEgGqqoBNm4yHeniYQy90jLEMoBPKykTSm0xTKhQRw4IgCPOQVAr44x9ZgOn0XOk0sHgxd917vSyknnuOPZkrV4pYKgX7ADWdL7i3lz25w8Mc/qC9v9XVwOHD7I0fHeWGCMDbjYxwyIoWu+vWGTEbj3MYxK5dxjn27LO8X0MDi9zBQf7N5mZelq98ueWW6yvMOIXSm7S3c9eI3fs7jalQRAwLgiDMQ/bv5zokm2WxqxR316dS3J2uBVU4zF7GTEayS+SSr7dWhzT09HAIxMiIyfcbDvM+ySQ3QBYv5utw8CCHqgwN8fpYjM+/y8Ve4AUL+Li7dnED5fBhToPX3s4Nl1CIr19fH2+vFAtor5fLt3Kl0Qy6fNqT7PPJ7HRCGcnXOuvs5OB3PauMfvBMY0tOxLAgCMI8JBTi93QaOHSIu/GVYpHldgPnnGNmOXO5WDz19/M6+wQO85FQiIVpMmlCDXR9rb23f/87i9NIhLcDWMTqrB3V1Xxee3v5vOqBb+k0N06Gh/lzUxOL2e5uDo1Ip7mR0tvLy3QZhobYu1xfz/v39vJnhwN47DFg6VIW3y0tXL62NpOJYs0a8QoLZcLeCotEuFXY38+jQTW5Lblix5gkIoYFQRDmIc3N7L08eJC9l0QsnKqrWbC1tbHoDQZZhPl8Zl89gcN8RKdH09kfamo4G4Our0MhFr2pFIte7ckdHGTvusfDnuL2dj6G02lmmSPibQC+Fg4H8PzzLHQ3bzZCORTiaxaJ8DaxGO+bSrHAdTr5s27gpFIcPzwwYKZq1mULBIzHWgSxUJRQiB8aAHcf6ZbfZAaz2ferqzOpVrq7jWHaBXE0yi25urpjY4anwHBFDAuCIMxDXC6ue/TgOaVYREWjLM4cDhZmmYxJ8dXczKI4N0xvGgZ3lxX9f1KpsWGLOh/w4cOmx3Z4mEVnMMj5fdvagK4u3vf557leHx3lVzbLdbdephRfB4DPczZr4oYBFtDxuLkG9fX8W4ODxhMcj3MZ9XF0yEsmw+u6u3kAXXMzi+meHi6jLv/ICH8/4YS5ce2EaWL//rG5AWtq+GU3mro6NsbBQQ5U111IuTdUb69p9QFstDrlisfDxrx/P6/Tglh7f3VibskmIQiCIBwvu3ZxnePzcb2SzXL9NDDA9ZHbza9wmOu8lhZ+6bCAnh6T7cBer1V6XLH2/B44wEKxthZYuJDr9kiEPemHDrGA9Hr5vytlGhAjI+ydHRkxQjkSYR2QTnMPcDxufi+b5Vc+0mmT5WNwkH8vnWYRHInwfg4HL4vHeX08bn4T4GvY2cnbvfWtHLoRjY7VE8DY/MeCcBTtDW5rM9MeJpP8oKiqYrGqHwp33803RDDIhrV4sUmX0tnJ+zscbLi6SwXgh0g6zcba2GhmjBkcZEPOTYQdDE55y03EsCAIwjxEd53r/MLaIxmJsEh2OFi4uVwsCDs7ue5bsoSF4sKFXAd2dIyt1yo5TZeeGOPQIeCRR4yjau1adl6NjPB5cDpZH/T3c3iC18sC1eHgc6RzN8dirA20EAbMu6aQENZkMqwh+vpYkHd08Cx0AJdDe/CV4muZyRjB7HLxtYlE+FrrDBVdXezd1jmPlyzh5YJwFHtgfDzOn9vb+YZwOtnY6upM4usnnuCbp7GRDUonutajQXt7TUJtr9ckOV+0iFvkhw+b39az/TQ28voZaF2LGBYEQZiHOBzGi0g0tns+m2UhCJju93gcuO8+MxhM95AuWmS8w42NXO9Vapou7QD77W/5XYvZF1/kgWzptPGgZjK8XikOWUileLkOWbDPGHc8JJN8nOFh1iMjI/zKZIwQT6f5errdRrsoZTzG9fW83b59LOztnmmAv+vyC/OA8cIMcgPjjxxhIbxjBwvhmho2tvZ2bv319XEy7dFRMx3ikiUm9revjx8SAMftpFImhCKd5pb00qWmlQewIG5tnbGZYkQMC4IgzEO0V1DHqtqxf9d1m+6Cv+cerv/cbhOLumGDcfrU1HAqsO7uyoshDoeBBx5g8auzbQBcp/f0sAPL4eBlqZSJ8bWHOiSTpid4qshkWHDrcUPpNL90aIvDwcI4kTDb65jhVIrXJZMs0oeG2KFHZCboCAbN9M3CHGe8SSt0Lt+BAX7PZFj09vfzskyGhW1DAz9A9u5lsZtIcOtwYIDXj4ywIK6vN6NvdSvN7ebPHg/fdE4ncPbZ/PDo7TX5/qZocFwpiBgWhCkgoxRSGYWdQwk83hvDuqAHFyyphstB5S6acJz0x9M4PJrGwionFlW5QDQ3rqn2JlbXZZEdJrz938NYtCaNv97ix3N/8I3ZNpk0oll7Rh0OrsN0doJzz+W6q7ub3wMBFpEeD7BxY2WI4mefBbZtGyuENdmsGXRWTOzqwWtTiRbgeprmZJLFrBbhulFjD8HIZoGVpyXRtDgLZ9SNpiYn1q3ja9XQYLJQVFXx9aqqmtoyC7OQUia40FNT6lx/hw+zQE2l2NAANpxYjL22kYhJWB6LsTD2etlIm5p4mc9nHhR6+sWGBo4n9vm4RQ0AW7aUbTSuiGFBOE5GU1n8eO8wYuksMlZX87P9cXRH0/iHVbUIuB3lLaAwaUZTWdz2Ughx68JWuwiraj1YXevBilo3fM7KvbbV1cCqMxO48F/DcDjN8rd9KYLm1Rn86dt+qCwLf+1pBI6NeU2nufu9vp7rt2yW69HhYSOck0nu8ZxNA+ty69zt24HvfS+/EM5lKr2+pZBKcaNCe6N1GbQQdrt5mfZSA8CWyxJ465fNqDhv0olDHg+WL/UA5EI0ytc2GmUxvHbtTP4joSzoQHfteQWOneBCj4pNJs0sMAMDJu4mkTBpSsJhvrG1+AVMzFV1NRtjKMQGtmkTh0L09fHDRMcK5874Mg2D40pBxPAsp7f3dhw48GkkEu3wepdh1aqvoLn5qnIXS7CxYzCOSOrY2rE7msad+0O4Zn0dHHPEmzgRKtF2s0qhI5JCKgusrnVjx2D8qBAGgNG0wouDCbw4mIADQGvAjdW1bqwOetDodVaU19jvB055U2yMENace00MqTjhr7eMn8w+Hmfh+9xzXM+tXs3OoljMjKPR28yWgXX2nuJIhHt6//AHfp+N6J5lnTNYe+m1uSkF1DZksfCEFAYOO9HzkgtnvD025hgJTwbPDcfw3HAM3ssIqwY8SHW54Y96sLK1cht1Qols386Gr5NN19SwSA2H+b2nhwXuSy/xsniclyUS3OLyenm9nkJRt86UYkP0eNgw/X7e1uVioa231QPhBgdNSMXevdyKXrOm3GdHxPBsprf3duzdey2yWe6bSyRext691wLArBcV84li3sG+WAZ9sQwW+efXrVYu201nFR7uGkVGAecu9sPrdGAwnsGe4QTW1XnQ5Mt/HQbjGTzbH8PuoQRG0yx+X9lchZeGk0e3cTsAe5snC6A9kkJ7JIUHu6J47wl1WFhVOdfZ41UY7XSiaU067/qtr4uXJIYBUz8mElyPHj7M2SYiEc6utHQpbzcbBtbpnuJIhMcDPfAA1/+dnVw/l4uFK9M4//0xHHzWhb/fxTEL689KYsHyDJ76jQ8AHZ2IQyn9Ulj3qhROuSKOVa9MwuUGMingnv8IYNlJfF1VFiAAsD2msk4FLEzAsTABlXWgFQ2z4toIU0Bul4eeDvHgQROqoAe+aaH70kvsHW5v55tXpyNJp02akUjEJCHX3Q9+Pw+uczhYUOvltbUm75/Xyw8Bl4uNdsMG3ubAAX5PJFiol7nrqHKe3POQAwc+fVRMaLLZKA4c+LSI4VnE5iYfTmzw4vZ9IXRHjxUWDxwehdsBrK71YOuC+RGYVy7bfbY/jqeO8FB5BeCS1mrcdWAEA4kMtvfHcd2J9XBa7jSlFJ45Esfh0RR220Sv5oleo4w8DsKHN9VjIJ5B20gS+0NJ9MZMYGjA7cACXx4X6yzG7SI8cUsN7vt2FT542/Ax6xtas3jdxyNoaM3ggVv86NzlLno8PXYmkRgbIuHxmG2mYNbUSdPezk6pVIpTiz39NMcH79nDY31GR8tXNgB4+7+HsXh9BlsuT+DwLhfSScI1/zUCAGhYmsFjPwzA62UnHHmyOOs9Uax8RQqL148NUHa6gTd8yqSxaH/agy3OGlQvS6JqWRJdyRRGM6ZV5xz0AA3lvTbCcaIFsJ5NxedjsXngAHtkdcoTh4O9vcPDLHpHRkz4A8CCtafHpBvxePiG9njYsrBqAAAgAElEQVR4mR5xqUduxmImVmdkhI1I5xKsr2fBvXYtL3e5+KUHE+hE5sCs6DoSMTyLSSTaJ7RcKB8uB+HqdUE83BXFjsH4Ue8iwN5DANg/kkKd14lVtZ5Ch5kzlMt2H+02Avy5/ji8DsJAgsXCSCqL9nAKK63zv3Mogb8cLk0Bbaj3wOt0YHG1A4ur3TinpRqRVBb7LWEc9DgqKkQC4LorkQD621246dJ6/MPnImhalkFDqxFKr34nV4obzgnhi+c1IDZSvDs9GjXpvHQ60UCABedFF01tPTeRcTY6Q4Se/GLXLpNGTYcwlhu7qP3n20PY8VfznDjzbXE8fVs1nERIJoErbohg4/nHNuDy8dIDPtSvJmz0eXHaCV4sXa/wma9nMOhMom5NErse9qDbB9x005T/JWEylGrYejIMnfv38GFg504WnLt2cctPi9zqak7xopeFwyaNWTjMy3SrVWd80ImrdU7hdNrE5dhTmXg8/NLxvzq5dWsrp09bvpz30QPnjhw5NrefzjZRxu4JEcOzGK93GRKJl/MuF2YfDiKcv6Qa5y+pxiPdo9jWc2yf6537R3D50gA2N/nyHGHuMJO2G0pm8Gh3FE0+JzL2ZLkAnugbew32DiexstaDAyNJ3PPysUlgX9VchcXVbvz6wMiY5Vsaj71eAbcDmxt92JxnXSUQDhtvaGTAiR//M1dCH/nlEFrWHqsOP/yzYfzsY7XobStebSSTXE8mkyYvbnU195QW6gWd6ADy8bJD2WlvB/78ZzPJ1Y4dLIITCTPmp1yse1USW18XxzO/P9aGNl04tnALT0iha4cb539oNK8QvuMjQWy4OI5TrkgcXTbc7cDQPjeGGkxq2CeeIBx83oVIxIX2B/1wOoF0AHj8ceDMM6f+PwoloG+AUqdz3L8fePBBnh0mFmORuW8f3xTDwxzykE5zazSb5e20dzadNgPj9ChMHRbhdrP4tccC25OQezxGBOsZX7JZEwKRybChLVxociwCY8VxKjU2AXdNjRnMV8buCRHDs5hVq74yJu4SABwOP1at+sqY7SpxoNJcp1iM8H0dEfTG0ji50Qe3A2gsEMdayUy37aazCqmsQpXLge/tLD1B6kuhBJYOuvD7PEIYADbWe9Hoc6K12oXOUfaqXLikGi3VxUMEKpFw2OQKTqWMMDy825VXDDcuzeJDtw7j15+rQSxM6NzlQiKS31OsU4Dpmc+6uniCqro6TidqF78684RmvOmc29tZzNoHxNt7WHOF9UMPAU89xf9XjxEq5wQT1fVZREMEX0DhH7/Nja7Nl42vyledmcSmS+M48cJjtz1yyIn9z7oxMuDAiRcn4PEB4QHC775YC7+Djmau8vvNpGJ2dMNFxHAZ0C27nh6O621o4CmOgWPTngG83e23s8BNpVjE9vSYfHt9fUZs6ikRk0neLhDgGyQSOTYtDGBuXI0W5kRj8wl6vVymYNBMtKG9yUT8H5YuNYnITz/dtHJXr+bMFR4P76dv4hnMKZyPcWthIvoRgNcB6FNKbbKWNQD4JYAVAA4BeJtSSlJ2TzFaFNjFQmPja3DgwKexe/fVR7/39PxEBtnNMtbUevD65TVIZLPYM5TEy5Gxte+z/XE82x8HAXjTyhqsq/OWp6DTxIKF70R7fAEO99yFYOyHcLvqEaF12LbvdjQf+CzWrPoiAGDv3muRyUah4EY80Y4XX7oRPYl6rG25DH63A7F0Fj4nHQ1BiKWzGIhncNu+EvJf5SGaVgWFcLWL0OjjjBBvWlmLHYNxLA24sXgOCmGAnTdVVSwc7XXdH75RjZ59Lgx2OPDub4XH7OP1A1f9By8bOeLAf76tDtFQfkGsQwp1PV9by3G6NTWmjtUzq+mpnIHioYPbt7Noi0TMgHi9bzQ6VlhHIjwp1rZtvF84XJon2BfI4sQLkzhy0In2F9xwOBXWvzqJ4V4nuveOrTKdLoVMGvD4FdweYNG6NA4960YmDVTVqjFhJYHGLN74qQhOLDG8IZfT3hQvuK7tSTdSKSDc68QdHw1iyaY0nv+jF144sHILe+U1emBjNGrGOPn9vFyYYfRoTj3b29CQmf1k/XqT9szn4xZdXx+v37+fxWQkYlKc6Zt4ZITDEHRIQzRqEoKPjprY33zo+GHt6c2XUNvlYuFaW8tCVt+wbjd3ATkcXO4tW9ioGhqO/Z1gkFteZcopnI9SXFK3Avg2gJ/alt0A4K9Kqa8S0Q3W909OffGE5uarjorafCP0u7q+Dx4qZJBBduWHiLCxgQVu0OM8RgxrFIA/dUTmnBjeNZTAXwe3Ap6tgGesN3gw+Qs83bEKRMBi52Voq7l57M4DwH0Dg3jVoio81hPD0oALq2s9eKhr7IC8qWZt0HtUdFe7HTijeW6PKFq1insxdT2q6854xIFtt/NAzyfvSuGMf8gvwmoXZHHSxQk8+evCg0KzWa6bn3qKB9dFIhy2uGkTZ1OKx/n39aytmnyhg9u3c4iD7k3W8wOk0+xoSqWMEH7uORbCL7zA4nlgoPTz8pYvFBasD/+kClsuT6D9eRcGOp047x85DCeVANzWLdy5y4V0Alh2choP/agKzWsykxbApbL7bx5kMnw+hg650fuSG9ks0NzK45caG7nREI0CmzezbrFnzggGebkww0SjbPzh8NiRpjqjQzzO4vKpp9ioh4Z4Wz1oDWCBm0iY6RDtyaYBM0Why8U3yXjdIloA54ZJ6JaT283LWlu5Nep0soH5fGa7TIZFuvZwF4oFLlNO4XyMK4aVUn8johU5i98A4Dzr808APAQRw8dFKd3F+Ubo5wphjQyymz2sqvXgTStrMBDPYH2dBz/YPXbkvn2wXSWSz3bv6bq04Pb9niuPfm7z31xwu8esmOuOSBodkQKejOPk0qXVSGQURpJZnNUyt8VvLg0N3IPZ0ZF/0gYAuPebfvQfciI6wkr5rV8Y61VfuLK0kWfhMPD88xzesHIlC9TWVuCSS3h9PD5WDOeGDoZCLID1Or+fnU9+v5lmeO9eLvu2bTxYbudOro8j+TsCClJMuJ77HrbJky4eu43b1pZt3Whs9YIPTF+utv/5UC02npfEQIcT+x53w+ViXaKng3a5WF+1t3ODBODz1dMDnHcen6/hYXbyrV9f3rRy85ZUioXvwABfPCKTBziZ5Pii3l6OB+7s5BslkzFdHA5HaaM/7VNHjofO3QcYcQ0YYez1stEsWsQGVlVlypXJsDh3ufihMgtigUtlssGKzUqpbgBQSnUTUcEOFiK6FsC1ALBsmQz8ykepOVknInBlkN3xM5W2u34cz+9Xn+vHmloPzmrxV1RO4lzb7U83omv/fUBVYTFcLl69qOrooMaFVU68e13dnJwuu1S7DYd5mmQ9lkY7mnQ9m80CyagDj1peYqdLHSOGX/WOOF71jjgevrUKD/zAj2Ss+PkcHeXMEsPDXM97PBxCqPMQA1wOPe2xdhr19PC+uke1pobrbD3m58gR9ji3tbE3uK2t9LAI/d82XZgEaHY2TPc84sYJZ7NH76+3VOEv3/cDILQ9yd5Eh8PoDp2LOJXiXvWqKvaqu93AK17B57K52XjS6+rMbLjlZk7rBZ39IRxmA47FWDz29nKeXz2/9sgIz1YTj3PGBx1CoT3CuV7fqcbpHDunuA6/IGLv7+bNbEjV1Wx0RDwgQGeE8Pu5pa27GsocC1wq017rKqVuAXALAJx66qmz80lTZkrNyVpohD6nVDenNt9AJWHiTJftnt3ixyPdx3b5t40k0TaSxAKfE29ZXYugZ/bnrbXb7pDrQuyt/kWZS1SYsxb5EfQ40R1N48zmqjkphIHS7bamhuutZcvYS6h7Wu0Z4uzewky68Pk695oYzr0mhsd+4cO936xGJlV423SanWHRKPeuBoNc9wYCRh90dfG2dXX83tPD24fD/Orr4xSqjY0mBGNggEVwb+/Epkt2OBXe/G8RbLVlYZhNdO504ec31uD898aQiBH+dmsVrGk0xqAUp3ZNJIyHP5nkc6VDRNvb2aF38CC/0mlen0oBV1wxs/8rH3NWL2zfzmEOhw+bWFyABWQ2y626ffv44mUy/NnlYmE8OGjSn80EubHCbrfpamhu5ribTZvM+gUL2Fusux+CQaClBdi6dVbEApfKZMVwLxG1WF7hFgB9U1mo+UapOVkLjdBftOg9GBi4V7JJVAivaq5CwOXArqFE3ljiI/EMvrdzCDec0lSG0k0MbaPdnuvwctWXy1wag99FqPM4ccGSajzRF8O5LX4QEU5u9OHkxnKXbnawaBHH7Q4P8/vAANe3sZjJyLRv39g6+AvnNOCCD0Rx9tX544hfdWUcRMDvvhbIu16jFNfxDz/Mv79zJ3upGxq4bk2nuQ6NRFjchsMc8pDN8vvICH/u6WGHW1sbe7gTk9CzX3x8AM5Z0hnT9qQby05OYdsdVQj1OtC8JoM//bcfyagDf/p2ddF9nU6One7rM5OEKcXnZ+dOHu+0aRNvG81pi0ejs2eq7FnDVA3u2r6dZ4B7+WU2eiKT0cHpNClOEgmT78/r5XWxGJdhphJh63RpTieLX8BMjtHYyA+NFSs4riYSYUPbsAG49FIzq01DA7ewK4zJPgJ+B+A9AL5qvd89ZSWa4+SLryzs8XXgoYccxwhcSaNW2RARNjf5sLnJh6f6YvhrgYkffn1gBIv9LpzU4EXNLPAS223X410Bz+LvIeW7AM94Z5c3+M0ra7A26Dk6GO4tgbmZDeJ4CQZZHMXjXAfHYlzndXZyXW3vzdW5g+MRB+79ZgD3fjOAz/x1ANX1xzrvznx7HNkM0HfQiWfu9hX1KEciHOMbDHKmiYYGE464YAHrh3SaPZexGJdT5+t3u1ko9/RMLN61qjaLFaek4PIA7/xaiXGUM8RP/6UWqTiQz/ML5B/cr3uxfT4+D9rpqMde+f3c0NmxA3j96/mc+v3svEul+Dz6fLy8AjXM9DCRRNbF0MHuySSfbC2CYzEWjrGYiVPKZEx4go7/0XG40wkRxyvpeGCvFdLnchlhXFPDk2esWwecdhqvDwRM7mCA3yvYgEpJrfZz8GC5JiLqBPA5sAi+k4jeB6AdwFuns5BzhUKxwYsWvWdMejRDZsx2wNjsEkLls7XJh+0DcQzEj33gtYWSaAslcSicwptX1cDnLD7713SibTedzSDsPBNDdDl6Bl8BlCCE37XoL3gkcnnBjBrj4XMSHAT4nA4sr3FjbdCDI7E0FlS5sKLGjT+8HMHOIXYJvmZZYIwQFoqjU346HFwnHznC9XMwyD26VVX8SiSOzcjwk+tr8cEfh+DI007TM9f5AgqP/KwKKlv8emjx3dXFdWxNDf/u6Kipm/UkIfrSanGsSuxMr2nKINicxfu+NwJfYPyd9j/lxu+/Xo2P/urYqapLZfCwA04XEBkkbLujCi4v4KlS2PeYG0PdTnziD4MI1HN6tpvfG0QqXvw8FQr/0JqlttYkIdDjnVwuPpcA6zs9D0IuVfNjpvjx0enO7JQ6VbCOCwa4RReN8r69vfyeTJoBcPE431QjI6a1aWe6Z4TR0yP7fCyGvV4TXxMIcItJp1lrbQXOPRd405v4gTFL0qFNJaVkk3hHgVUXTnFZ5jyFYoMHBu7F+vW3HPW6AQ5oIWzfTtKlzT2cDsJ719chmsniOzvyp+puj6TwrRcG8bbVtWWbyvnAgU8jjFV4MfjghPY7KXw+OuJhvOPMK8csj6ezSGYVhhIZ/LxtJO++rdUunN3ix/KaY/+z/Ty8dnkApzT50Ox3wT1H44Cnm7POAp58kuNw3W7OS6tnaE2l+N3pHOuk6tjhxpcvbEAmDXzh0cG8x738+iguvz6Kz53VgGS0eGMum+U6Nh5nYe5yGUdVNGriiXWmp1JFMABc+s+jOO+9E0uX8MPruKK/cevYcKWG1gzC/Q6c854oLrqOj5nNYEyj4G8/rcKjt1Uh3F/8P//fN9ajaWkGnbtcKOQNtqPHMdmvg1ImEYHPx07MeJzPm8vFvdvr15sBdmvXAvfdx45JzeLFvFzAsTEk9uXFxN/+/ex+11kbamp4YozDh83sM6EQXyTduoxG+QabSJD7VKBFcCDA3TE620MsxuXx+Xib2lr+Hw0NwIknGu/4HBLBmlkSKTU/KBYbbPf4PvRQ/geopEubmzgdhBqHE9UuKppm7c79I3j/hjo0zfCMdRml0JF9NQ7U/OeE9jsjtAAEIJE4tpL3uRzwAaj1OHHDKU3IKgUHEQ6OJHF/ZwTLAx5ctqx43KnGQYRWCYWYFLo3+KmnWAgPDvL3gQGuD1ta2HGVSJheWzv2SSWK8YVHB/H5cxoKzlhnRw+Y1ylRw+FjxV+p+OuyeO2/jmLr60oPJt75gAe3fby24PrBTla9f725Gn+9uRrkUFBZwiUfHsXJlyTwp+9U48X7S8sbHg870Lmr9B4fp/NY3aTDHBwOdiauXcvf9+9nb++JJ7LmqavjzwBw8smsc3R+5xUrSi7C3KdQGrB8+f60hzQUAh57jL3CuuW4fbvJHhGPc/aFRIK37eri93we4elG5wqureVJMerqTHhGVRWL4ESCR2MuXMitKp9vzgeWixieQQrFBuemQSt1O2Fu8ZbVtbj7YBgBt+PoVMC5/HD3ME5d4EO1y4EN9V7Ueac3lrg9nMIdbSHAX5oQrk4/g5bk99GQuveon6sUu3VYfd8raz24bmOeGYuEKUf3Bu/fz0JYZx+IRNgz29jIdXpdHdePemBWPu75RjXOe28UfQecWHVqftv9/N8G8cf/9iMRITz1W1/RjBOayQ6gdzgV3nBjBKe/uXQR/MAPqrDnUQ86XpxYtahDQO7/TjXu/07xQW7Hg9tt0t/ZZ771eExKV4+HY76zWe6l1zPmnnACcNJJHNLZ3c293tqDrB2E4zk+5w3BIJ8c+1SGnpzeqe3bOfQhFGLPb3s7C8hDh/gm8vv5RPf1mZZKXx+v00HwMzUoDjBdCjpuZsECTvjtdLLYra7mMtfXs9GMjLBROJ2mtQXMaSMRMTyDFMoGkZsGrdTthLlFi9+N6zbWg4jw3R2DGEnl9xg8fYQVycPdUbxpZc24OYwny57hBH57sPQBRi2eAawMv1nstkKIRlk47dtnenZjMa7/PB6uM+vreXkwyHX5SP6IFmy7owrb7vDBW63w+Ufyh0wAwGX/H9vGG24cxZcuaEB0eOrj4IkUrr9zuOQJQQDgO1cH0blzdvcuuN1mEjHATELm9bKOWbyYBXBXF2ueE07gTFjLlwPnn28ySWgHZyBQfKKTeU1TE4vW9na+GQYHgT/8weSue+EFvnmiUZMEOxQygeyjoyx8lWIhqdO0zKQXWCec9nrZ46u7XFpbeSBcIMDTUAYCLOzdbjaWQIBbxyMjHCIBsHE0Nc1pIxExPIOUmg1CskbMX/TAr3esDeLJ3hi2DxRwxVn85mAY16x3os7jgM91/MIins6iK5rGnfsLqJ48XNJajaYqF5ZWN6Kv7xax2wpBhyDYBVFVlam79Uyr6bQZOH7wYGHvMEBIjBJu/UgtTntjHCdeUHwA0L89MIhvvKEeQ90OZItknCiVxqUZbLoocVRwj8eBp1149h4f2p50I9Rb/mwtxXA4uEHi8fD5j0RY17jdJq7a72ePvs4VfeQIOwDXrWMvvybX8QlUzLwIM4OOHdJ5/Q4e5OXd3bwuHOaTPTLCAnd0lEXv0BALYHt+Px1+MFM5ggEjgrVXt77ejJJtaeEJMwIBXrdlC++zdy+XvamJBXF1NRtQPM5G19zMD4A5bCQihqeQUqZULjUbhGSNmN/Ue524bFkAlyytxouDCdzXXnhO2Vv3cq329tW1WFnrwWgqC6+TJjSpRG/v7dh74Kt4zFfaADmPg/DmVTVYkTO4Tey2cnC7jeNHi6NAgEVyTQ3X6V1dvJ2ecVWvL9bDu/dRD/Y+6oE/mMU7vx7G6tMKZxH5+N1DiA4TvvqaBqTiQHBRFqEeB0oZTKZxOBU2nJvEu75RWi/G7r+58evP10yLV3q6cLn4mmhtVV3N1yUWY63icHAPfVOTmbxED0hMp4916K1ePXVpdOcU9kwSOtvDwYN8Qru6TDo0nf4slTJTEetMDNr7q6c1nk4hrDNC6BCIVMrEBLvdbChr13JrqLaWcwKvWcM3fEcHl72picVuOGxaTZs28XJ7Zow5biQihqeIUqdUFoSJ4CDC5kYfTm7w4lA4hV8W8dj+cv8I3ryyBr85GEaVi/CBDfWoKsFb3N1zB37SfSngK20K5Q+dWF8Rs+MJxfH72dkTibAHUac3046u3bvHbh8MGodST8/4A9miIQd+eF0Q5FB4/80hrHpFflHgr1P4h8+GkYwRTntTAi/c78HPbyg8gM3OspNT+NCtoZK2bXvSjZ9cX4t0srIyjng87K33+1m7aO2jFK+rruZ3j8dMZqavjZ6zIZ+OCQbnvL6ZOPZMEjr5cn+/mQlOTzQxOsqtxVSq8I0w3SERLhffkDqZdFWVmY2mtpZv6jVrWNhu3MhlbWw0XUE1NSYWuLWVPcnNzWNbR/PIQEQMTxGlTqksCJOBiLCy1oMzm6vweG/hFFH/a8X4RtMKj/ZEcXHr+BkZ7jy8nrP5jcPHNjdK6rI5hO4uB7h+bGoy0/e+9BLXsfX1JmXXihXcExyN8naDg6VldlBZwg8+EMRNzw4U3GbzZSak4uRLkrjri9lxU7EBKEkIP/VbL37zpQCUqjzb9flY7OpBbtXW+Lx43GTkqq831ykaNbmhvV6eEXfhwjmdBGBqyXWh6wwQ4TAbfDRq5i2f7jzAxfB4TIoQpVjEOhxG6La2AkuWsOFs3QpcfPGxE4lo7690DwAQMVyUUsIeNKVOqSwIx8O5i6tBAB4rIog1zxyJI9v5dmxZ+c68dquUwm37Qog5lhc9Tp3HgfdtqBchPAfJ7S4PhbjODAZZYCnFdf+iRSywFi1iZ1kwCLz4Ijui0ulSRDHhU69oxL8/U1gQ23ntv47iz9+tRmQwvyCuacrgU/fnz8tt51efDeDZe7yYSNjFbMHlYi3W3MzCdsUK1mCJBJ9z/b50qdExPT38ubGRU8OuWCGZIkrCfhPomCGdrNnhYCFsD4eY7hhgPa2gvrHs6UN0+MPixdzSSadNa0mnQWts5HVLlgCnn87HKBQbI4YBQMRwQfKFPezefTVCoW1Yt+67x2wv6dCEmeKcxdU4vbkKdx8M42C4+KxuL3j+C9hzLqr3XY+1a/8Tzc1XIZHJYl8oiWha4XCBFG4AsDVxNS48/V44RQTPC0IhrvN1r2tDA9ebPh9/bmjgOvisszgvsdfLcwzoGWbHQynCjVub0Lg0g4/fXVzInv7mBPx1Cr/+XACJUSOIG5dm0LoxjStvKh4f/JWLGgoK6dmG1jfZrInF1mOgdI/34sXG+ReLsdbZtIkbLiMjJozijDP4WICJHwbmdBKA0igWIG0fMBePm9bHM89wCjWXy8xqohM9T4dXWOfIU4p/U8+momesA3i5jt/dvJkNYXiY92tp4Rs4EABOOYXX5Q56k9iYgogYLkC+sAdAoavr+wgGX32Mp03SoQkzic/pwFtW1+Lpvhge7Co8ej5DQTxXux0AEHvplfCNLsG20Kaix3Znu3FS9G3YvO4zIoTnOFoHdHZyT7AWYA4Hi60TTuAxRAsXmrDD4WFO1XXoEA+293rNYK1SGOhw4qZL6/HRXw2jqrawS3nTBUlsumAQz//Rg3u+EcAr3xbDhdcW7xF58H+q8Jeb/VOSncLpNHl9HQ7WKjU1fA5iMTOOSjvs9FgmPTmJw2GcifZj6pS1OjWa3jeb5WPqbFguF2/b2sqTZOjQiNpa7vl+/etZ4+3bx/stX855hHN7w+d9pgi72B0Y4It4+ul8UkIhNv4DB/jk+v3An/7EojIcZiPX0yU7nSY2ZSIzv5SCThTt97PBeL38m1VVphuAiOOAW1u5/KefzsYyMMD/LZlkIb9yJd+8EvowIUQMF6BweIPC7t3vwoEDnx4TNiHp0ISZxkmEM5r9CLgd+P3L47vmngk8AYwTYrlu9N1oce7CqnViu3MdPXA+EjF5hrUQzmbZ2zg8zPXpggU8qN7j4Z7Xvj52RG3YwF3zehB7PF5aD/LIESe+fFEDrvxKGCddXNzLtvmyJDZfVjh3seYzpzcic5wiWKcp0yGZNTX8f4jYIVdby1rF7Wa91NHBjQCv1+QB9vt5fNXoKG+bSpm4a6+XP2ezJjtHbS2f/+FhM4mGPc/zhg2sb3SsdkMDXwMdB3zqqWP/g2SKsKGNvLPTdGO43Tw6dOVKvkB9fRz7k0qxMessC6GQuZA6Pcd0TJbhdPJFdbv5gtXWsgjWAly3rAAWu2ecAZx5Jpf/yBHuAtBebZ+P06XN64s+OUQMF6BQ2IMmX7YISSsllIMTG3w4scGHaCqLH7zw3LgxwIW4ck0tVtTcO8WlE2Yr2pObmze4sdFMmlVXx4JNe44BrqO7u1kbbNhgwiqHh3mb7m6zbTGyacIdn6wFPgmsfEUS1/6g9NzWuXzqFY3HNUCuupr/97Jl7AVvbWUN1NPD50APzm9o4O9VVfwfjxxh0RqLmTDTBQv4eH//O2fjclm1rMfDxw8EzEBEt5vFttZbfX1mW7+fY34vuIBFsn22OKB4HLD0hltEoywUX3yRZ4oD2JhdLp5QQyk+6YEAX8zdu02LTk+jrGOE7WnT8qFjfJXiC6tTnenWTz70hBh6BjgdKlFba1pQOmtFIMDdM62txph0V42eQWXedwNMHhHDBVi16ivYvftqAIW7QyRbhDCb8LsduLJ1D55suxG7/HdMaN/3rAuipXp2z8AlTC06jlRnV9JowRUIsI6we44B012vRbQOJQgGWbw1NQE7d/J+pTrRDj7jwY1bm3DRB0fHDYXI5bOvmrgQtntg6+t5HoITTzT/fcsWDgHZs4e1SjBoznT7mMMAAAz0SURBVNc55/D3aJS3yWT4v3Z0sCdZT3N8+umsr55/nrepr2eP7pIlHNrQ3c3Ox74+FtBLlgBtbSzAvV4+j+edx+GfbW1jJ0cBJA64JPx+DiPQUyeGw3zSq6rMBRsY4PRpfX3cKolGuWWihbAOiRgvVZrbbbpVPB7j1dWTbjgcbGDZLH93uVj0aqNrbOT9lGJjqakx82c3NrLRtbayYWzcyL8p3QBThojhAjQ3X4VQaBu6ur6PYoJYskUIs4nm5qtwBgDfvovxrP8+gMa/xT96UsOUzF4nVBb21Go1NawTamqMg6mpiUVYrufY5+M6+oUXWATq2We1Q8vvZ7F58CA7rZLJ0gff/+X71eh+yVXyBBo3bm0qaTunk/WPHphWX8//v6qKwz2uuIKX2c+B1h1dXeY4ixfzfwd4/5YWo0WCQSP+9Tk891xO9drbazRPXR0f+8kn+Rx5vexxXrOGByfu2cM66YwzzBTKMmPcJAkG+YK63Wyohw+z0dpd8fE4v0ZGjBhOJMwkGhqd3NmOHlSn58XWBmZP/BwImIwPeqabeJxvFB0LU1PDZdUzx2mhvGSJ6Z6pqWHDyb340g0wJYgYLsK6dd9FMPhqKw44f8iEZIsQZhvNzVfhkuarsNlKDdiVOQn7qn+cd9sPb6oXITyP0Y6lxYvZ26vDFnXdWlc3NlOEFoqRCHssjxxhsej1mpnr9AAyp5OdWuk0647BwdIG4e98wIsbt3rhcCq882vhvNM673vCjR/9U2kCYNEi1hQrVrB26ezk8urMU+vXcwhmbe2x52D1au5NHxxkwbosz+NeaxG7MLafwy1b8i9vamIPcXv72LkQTj2VhbFd34gDcJKEQnzR9MC0ZJJPolLcEhoaMlP06amVMxk2lNxujXyD5rQQtid31rPTEJnvkQgfXxudw8E3nU4lMjLC8cDaQ5xOsxFUVfH6fDenMKWIGB4HHQecm2oNkGwRwuzGbrtNe1dhmLYg6VgEX/YAgmo31q+/BTVuCfGZ7xRzLK1ezaLN42EdoQWbx8MicskSznPb3891vZ7NrqqKvwMmM4IexzQywhplPLIZwm0fr4UvkMXKV6TgDyrse9yNkSOlzX64aBGwbh3HNS9dagatnXCC8Yq3tPB2xWabXbYsvwjOR6FzmW+5HvxWX1+a11ccgCVgbzH097PB9ffzOntrRnuBdTxuOMzGq+e7zid8HQ42ZJ1Y2+02c2Frl7/TyRd09WoTHK4HxA0NcWvxjDPGzvwWibCHeuFCc4PV1fExhBlDxHCJSLYIoVIZa7uPWrZ7i9iuUBLBIHtO7ToDMHGsgQBrgHCYhXA2yyKvqopDKfx+FsR1dSyg+/o4fas9/KAY8YgDux/2llzeNWuAs8/m94ULWQj7fKyJ9EA4u9Ov3CEH4vWdIvbvZ/GrB8B1dLBxDg+bdGgLF7Ix7tnDJ9zhYFEbjZpYHvuANz0ozuk08T+plBnh6Hbz8davN6EYDge3HBcu5Hx3WjT7/bxuyxZufQFjL7oYQVkRMTwBJFuEUKmI7QrHS65n0h7H2trKeqG52fTonncei+G9e1kvLFtmMkRt2wbcdRevn8r5C04/HXjve9n7q51sCxZweewZp2ab7hCv73ESCnHqND3Ss7ubW1sbNpjEztXVnE9Ye4XjcRavgEljBhjhrL3DTqcxXL/fxAMtW2by6Z10Ere44nH29C5dCqxaxSEPwNhUILW1+Wd/EyMoKyKGBUEQhAlTikfz7LN5wojcbc4+m2N4f/ELdugNDLB+OR42bgTe9z7ODKGpqyse5ytUMHbj6+lhIayTMetsEKEQx8L4/dwlkcmwONYtOe0N1lkc9CA5HTOswyB0Au6mJha/DQ0mHqilhY2uv98kgl6/3uT+tU8FCEgakFmKiGFBEARhUpQiKgttc+WVvPyxx1hHhMPAI4+wQ6/U7BMAO/y2bAE++lHgLW+ZfV5fYRrInWZvcJBTdujk2YnEsWlQdMoye+q0eNyEQrjdJh1aLGby7+nsDkuWsLe3pYWX+3zcFXL++WYiD3si6EBgbIoRoPwxOUJBRAwLgiAIZeHyy1lb9PZyiOcrX8nZFbq7OYSivX2s5rFTW8vaZMsW4NJLWQgD4vWd8+hZ5exob7DG5zOzpSjFYQ0NDWZ65VCIt1eKt3G5WBhXV7Mnd2CAf8PhYO/vsmXA2rVscGecweIXGDvyUk+AodGD4KR1VhGIGBYEQRDKhk49dvLJJt5Yv+/YAXz72yyMQyHWLs3NHI/scrG2uOwyDrsQ5glRk9HpaCjCwAALWZ2nNxRiUet0spe4v9/k/OvrY0GcSBiBumABG9TSpWZq5Bde4O1qazmmx+/ncAid/DmXQsJXWmcVgYhhQRAEoawU0gstLeyMe+YZzmm8YAEvA9hht3at6Ix5h4651XOE9/ZymERVFWdwSKV4vZ4+ORZjj/CCBSyQBwdZ+Lpc7EH2eHg/v58N6uSTWWQvXszLdLjF6tXcciuGCN+KRcSwIAiCMGvRuY6lp1kAwAagc/lFo/xqaDDr7cv8fg6hcLnM7DHV1RzPaxfPa9awCF65cuzkFhLiMG8QMSwIgiDMasThJoyhuZmF6uHD/F17i/1+kyKtuZnfPR7uTqiq4jibVMrMQBcM8j4nn8z5AXNTj4jhzRtEDAuCIAiCUDn4/ezdXbKER15qGhv5dfiwmTjD7+cQiQ0b+HtTE8cOL13KaUsaGjgvn4jeeY2IYUEQBEEQKgc9nzbAmSJ6e02Gh9ZWfunZ6Hw+/q5jbXTcr4Q/CDZEDAuCIAiCUFno7A06JtjlGrsuX6B57oxvgmDhOJ6diegyItpLRG1EdMNUFUoQBEEQBGFcPB7O96tnehseZpEcDHKssIheoQQmLYaJyAngOwAuB7ARwDuIaONUFUwQBEEQBKEg9pzDpSwXhAIcj2f4dABtSqkDSqkkgF8AeMPUFEsQBEEQBKEIOotEqcsFoQDHI4aXALAN40SntUwQBEEQBGF6sQ+k09TVSWiEMGGOZwAd5VmmjtmI6FoA1wLAstwcfoIwixHbFSoRsVuhUpmU7RaaBlkQJsDxeIY7ASy1fW8F0JW7kVLqFqXUqUqpUxcsWHAcPycIM4vYrlCJiN0KlcqkbVcGywnHyfGI4acArCWilUTkAXAlgN9NTbEEQRAEQRAEYfqZdJiEUipNRP8M4E8AnAB+pJTaOWUlEwRBEARBEIRphpQ6Jsx3+n6M6AiAl6fh0E0A+qfhuNNJpZV5tpR3uVJqxvt+xXaPUmnlBWZPmWfcdqfRboHZc15LRco7eeaS7c6m81oqlVbm2VLeku12RsXwdEFETyulTi13OSZCpZW50spbKVTaea208gKVWeZKoNLOq5RXACrzvFZamSutvMBxzkAnCIIgCIIgCJWMiGFBEARBEARh3jJXxPAt5S7AJKi0MldaeSuFSjuvlVZeoDLLXAlU2nmV8gpAZZ7XSitzpZV3bsQMC4IgCIIgCMJkmCueYUEQBEEQBEGYMCKGBUEQBEEQhHnLnBHDRPQfRLSHiF4got8QUV25y5QPIrqMiPYSURsR3VDu8hSDiJYS0YNEtJuIdhLR9eUu01xEbHfqEdudfsRupwex3elHbHd6qGTbnTMxw0R0CYAHrJnxvgYASqlPlrlYYyAiJ4CXAFwMoBM8pfU7lFK7ylqwAhBRC4AWpdSzRFQD4BkAb5yt5a1UxHanHrHd6UfsdnoQ251+xHanh0q23TnjGVZK3a+USltfnwDQWs7yFOB0AG1KqQNKqSSAXwB4Q5nLVBClVLdS6lnrcxjAbgBLyluquYfY7tQjtjv9iN1OD2K704/Y7vRQybY7Z8RwDu8FcF+5C5GHJQA6bN87USGGQkQrAJwC4MnylmTOI7Y7xYjtzghit9OA2O6MILY7DVSa7brKXYCJQER/AbAoz6pPK6Xutrb5NIA0gNtnsmwlQnmWzfo4FSIKALgLwEeVUiPlLk8lIrZbHsR2jw+x2/Ihtnt8iO2Wj0q03YoSw0qpi4qtJ6L3AHgdgAvV7AyG7gSw1Pa9FUBXmcpSEkTkBhv17Uqp/y13eSoVsd2ZR2z3+BG7LQ9iu8eP2G55qFTbnUsD6C4D8P8AnKuUOlLu8uSDiFzggPgLARwGB8S/Uym1s6wFKwAREYCfABhUSn203OWZq4jtTj1iu9OP2O30ILY7/YjtTg+VbLtzSQy3AfACGLAWPaGU+mAZi5QXInoNgG8BcAL4kVLqK2UuUkGI6CwAjwB4EUDWWvwppdS95SvV3ENsd+oR251+xG6nB7Hd6Udsd3qoZNudM2JYEARBEARBECbKXM0mIQiCIAiCIAjjImJYEARBEARBmLeIGBYEQRAEQRDmLSKGBUEQBEEQhHmLiGFBEARBEARh3iJiWBAEQRAEQZi3iBgWBEEQBEEQ5i3/P/tXr12Bl6KCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41bf5588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 2000 - 1.9972558772627285 0.08601817697550526 [0.06126967 0.39897382 0.39423513 0.39553675 0.40388337]  -  1.0000005960462701 1.072438377263964\n",
      "1000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ad05c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41c55748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ea4c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25 1000 - 1.6769662189885894 0.3815682149414521 [0.06281737 0.3798245  0.36434355 0.3677373  0.40271112]  -  1.3629303401322157 0.9723425363088344\n",
      "500\n"
     ]
    },
    {
     "data": {
      "image/png": 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wWmW074E8jlsQyAh4FgRBEISCQVwU6C6llFTTEgRhShHPsCAIgiAIglCyiBgWBEEQBEEQShYJkxAEQRAEQRBKloyeYSKaR5xLb7uRa+4qY341cTm+3cZ71eQ3VxAEQRAEQRAmjoyeYSKaA2COUuoVIioHl/j9IDihe7dS6iYiugZAlVLqm+n2VVtbqxYsWDAhDRdKk5dffrlTKZWuUMOkILYrjJdC2K7YrTARiO0K05Fc7DZj0Q0jp+MR4/MAEW0HVzP5ALg0IMD599aD0xulZMGCBdiyJWm2H0HICiJKVzlt0hDbFcZLIWxX7FaYCMR2helILnab0wA6IloA4O0AXgJQZwhlLZhnp9jmSiLaQkRbOjo6cjmcIBQUsV1hOiJ2K0xXxHaFQpG1GCYiP7hM4FeVUv3ZbqeUuk0ptVYptXbWrCnv3RaEvBHbFaYjYrfCdEVsVygUWYlho6zfXwDcrZTS1VLajXhiHVd8dHKaKAiCIAjCRNLXBxw5wu+CUOpkjBk2aov/GsB2pdRPLYseBJcbvsl4/9uktFAQBEEQhAlj716gt9ecrqwEFi8uXHsEodBkFMMAzgBwOYA3iGirMe8/wSL4PiL6LIAWcA11QRAEQRCKlL4+FsKDg8DICODxmPMDgcK2TRAKRTbZJF4AQCkWv2timyMIgiAIwnjp6wOCQcDnixe5wSDQ2goMDJjzysuBhgYRw0Lpko1nWBAEQRCEaUK6MIhwmIVwMAiEQoDLZc4XhFJFxLAgCIIgzBD6+tjzq0Mg/H4WxjoMwunkEImDB1kAO53AvHn8LgiliohhQRAEQZghvPUWC11NeTkwdy57ggMBFsBDQyyOBwZ4eXW1eIaF0kbEsCAIgiDMAPr6OPTBysAAe4J9Pp4eHgZ27wYOHwaiUaCnB4hEeL4glCo5VaATBEEQBGHqyCUfcDDIYRHl5fy5t5ffXS5zcNyRI0B/P8/Xg+z6+3m+IJQq4hkWBEEQhCIk13zA2vsLsKd3cJDFsddrzh8ZAdra2COsFIdMxGI8XxBKFRHDgiAIglBk6HzAmsFBoLOTB7rNn598m0AAsNuBPXuA7m4zDri5GVi4kJdHImbcsHWQXSQy+d9JEIoVEcOCIAiCUGQEg+bn1lagvZ3jgYeGWMym8hB7vSyi29sBh4PF8549wIoVplju7GSxHYsBo6M8z26fmu8lCMWIiGFBEARBKCDJCmTokIfBQRazWhxHo7x+Kg/xW29xeMWRIyycAwFg9WqOCwY4RCIWA2y2+Pe2tsn/noJQrIgYFgRBEIQCkSouOBDgzwcOmEJYvx89yqJ47VpgzRpz274+Fs9vvMHe31iMvcNDQ8Cll5r7iEbZuxyNctxwNBrviRaEgpGqdGKu6+SIiGFBEARBKACJccEAT7/5JsfwVlcDTU3s5Y1GeXl3N3DoEAvizk6epwVxMAhs3cphFXpgnMvFXuS9e1k8+3wcGhGL8TY6VMI6+E4QxkW+YjWbEaO5jirNEhHDgiAIglAAgkH25OqBbACwcSOHLgQCrCnsdsDt5s+HDwMbNvA21dUseru7zcFx4TDwj39wSIQWu8PDLJx37eJpm433NzLCglvv3yaJVoWJIF+xmurJUJdOzHadPBExLAiCkAKlFCIKcNoo6fLHWgbhshPKnTasqfWkXE8QAL5n69jc+noe5HbwIIvivXvNohkeD4vY0VEWvk4ni9dXXmHxS8TvOjfwq68C69YB+/axYI7FALIp2OxANEwIh00x7HAAdYsjOO2cYfQcsaHrgAND+9xwiBoQxst4xGqqOB1dOjHbdfJEzF8QBCEJMaVwz+4+tA5FUO60od7nQJ3XgXofv7wOwtYuMznribWeArZWKFZ0j3F7O6c401khurpY4I6McJW43l5TR0Sj/Fkp9tqGQuwF7ukxwyVGR1kw79rFA+zWrePwiZERoG5JBFfe1ge3X6Fjvx2HtjtQU+5A66ADXr8D9kAUq989CgDY+bwLj292o6ysML+PMINIJ1b1e6rQiVRxOtb52ayTJyKGBUEQknAkGEHrECdfHQjHMNAXwu6+UNJ1yxwEu3iFhQT27mUR29IC7N/PAtfrBbZsYeEaDJrhDPPmAWVlnA1Cz4/FzJRnfX2mENaEQuwJHhjg6dFRDpU444Mj8FUqAED90ijql0YBjOKu3QDmARd9y9xH/1EbwmFuoyCMi1SitL2djbetjQ153jzgzDPj19EjRhNDLKzCOZt18kTEsDAu2tvvxr5912J0tAVu93wsWnQD6uouLXSzBCEjyWzXU/VxNA+E0TwQxrae0az3VeGSJK1CPH19wLPPcgzwjh3s1Q2FzPjfo0d5GuB43SNHOIRhdJTfHQ72DIdC7O1VKvlxRkeBXbsV2oJRDM4K4ZKfhLHo5HDqhiU8s4302uB0stdaEMZFMrFqt7MQ3rwZ6OhgY9ajPC+5JH77xYszD75bvJif3Lq7OXA+VQWaHBExLORNe/vd2LnzSsRi3AUyOtqMnTuvBAARxEJRo203pFzoc1yMfjoTL7UuxcjhnqTrz/LYccpsL9qGI2gPRtA+HEE4Zi5vKJNLqRDPAw8Af/gDx/kODaUWswB7gEMhUxxHoyxybTbebuy2CjXzYlhyagiLTwmj4R1h3LlTAXOBRXPj1/zbTWVwe4AzL46g6fgIOoejcYL46C4n3G7OWiGUMMlEqDXI3evl4PVMGSK0oLUmrt66lQPaBwdNY371VWDu3LEe4kxYB+h1dKSvQJMDcgUX8mbfvmuPCWFNLBbEvn3XihgWipq9+67FbveN6HB+HKDMw+hPnu3F8TUeHG9Mx5RC92gUbcEIogo4rso9uQ0WphVvvslieMOG8ZU5jsXGzgvURfHJm/vRsDw6dmEC0TDw+uNu2KI2fOw04HMrga1vKNzw3xEMOyLobrWjd78Ty5YB556bfzuFaU6yDBAAG/LAAIc5AMCSJbzM5QJWrTJTnlhFdF8fx/qEQlzne+dOjgvq7eU0Jy4Xr+d08uhR6+A63Q6dYqWubmwibckmIUw1mUIgRkeTB5mlmi8IU4XVdl3u+ShrvAUVleejqdyJYEShKzILHf5PjNmO1DCaKiqwoNyJWo8Dr3QOw2O3YWWC2LURodbjQK1HLqFCPM8/Dzz0EPDkk+MTwgBgdyqsODOEzhY7OvbbUV4bw8kfGkkqhMscBEe/C3+/04nuXoW3XTiKN55wY7jfhtpaDtMEgDXHE5bUOrF+vRMDA0BtLXDiiVylTihBWlp4BKbHw+IV4BCGwUEWwjro3edjb69SLGj37GEB2thoitdQCKioMFOkhMN8EsRiLFiJeB0iPl4gYGaC0EK3tdUMgu/o4HdrIu1kSDYJYbLIJgTC7Z6P0dGxgWZu98TE8AhCLiilcGgogmDfQ9jW/FeUh3rhgEJbdAV2dZ0KdPWbK/sfPfbRGWvHrNA9CESeQ62jHWcs2XVs2ZKAayq/gjDNefBB4LXXgEcf5dCIbHGXxTBneRTD/YTKuhh2b3QiFiV86NpBnPT+1LHrLa878Nrjbqyc7cTtP7PjnnsIhzZxj/Qrf/Mey0ZRXc1aBTAHytXXs/bR+qelZcLCL4Xpwt69LGq16Cwv59CFkREWp9u2mSM9Dx9mo66q4jjgN94AamrYkBYt4tQmhw4Bs2ez2A0G2aiiURaqfj97hnXaEr+ft9WD7nTSbS2ENe3tpudXskkIU002IRCLFt0QJ5gBwGbzYdGiG6a0rYIAAE8fGsKWjhEAZwLeM+F3bkF1+EG0eK9Lu11V5AnMH/1fsNl8WLLotqlprDDjaGnh11NPsU7IFrtD4d/v6UXNPDMm4vFbfFi8Nowlp6YZCAfg6dt82LXBhYZ/Zf3R2MgON6fTXMfhYP2iNci2bTxYLhplB180ytPbtokYLim0J9ZjSQk5MMCC1OPhEZ27d5t5/jo72dPrdLKxtbSwcdXWsifY5+Ppjg72HtfW8raRCIvrE0/kPICjo9xNMWtWfHiDz2c+sVnxeEzPr2STEMZLrlkfsgmB0NtLNglhMklnu7t6R7GhbRjBSAz94fgAy0HHWgw61mbcvze6E253k9iukDPWcMnNm3nA3KZNmbezOxTWfWYYp/zLMCpmjR1Z9+4vpegOTuDofs5i0m90eixaBCxYwA66sKGj3W7WHjpMYmiIB+KHLTo7FMrNky1MQxIrvlhDDsJhfmlB2tHBRnToEHt8e3tZ1EajnAZleJi3s9vZeIaHeQRmNMoD7UZGWPQSsVD1eHi9+nrupliyxAzL0II4EOAYYe2lBthT7ffHe36zyTiRByKGS4B8sj5kGwJRV3epCAhh0rDargIwMtqMf+59EHuPnIeoyj2d2dlzfOgYieItS9q0C0+6BZVuSY0m5IZ1zNFf/gI8/DDw+uup1lZweoDzvhjEWZ8czut4j9/iw9suGDVyBgOtbznQe4TtVusapxN4z3tYh7S2slaZMwc46STu0Qb43emMF8NOp7lcmOakGtC2f785ItNmY89sRwd7gkMhFrJOJ8f8NjezwNUxvpEIbzM6atbxBlj4hsN8jI4OfvJyOrkrwuXi461YwevpFGvLl5uxOUB8vK+ODW5vN8VyMs+vFs8TiIjhGYzpURsrajNlfZAQCKGQWG1XATjkvhqtnmvMFdKkqUpFwDGI0+trAQBzfA68dHQYb6/1iBAWcsY6qP3++4G77mLxmYi/OobP396H2QszZ35IxzN3eLH+1z5suMeLj/5wAPVLI/j7j8ySceXl/O7zsXf4oovYCRgOc2/1mjWmc62hgQfLHTzIusbjYa9xQ8O4migUA4lZIfr6WITu3MkCUxtBdzeHMjQ3c2hDRQWL0lmzzPmHDnGoxPAwi9xIhPelBbXdblaE0e+1tRyPU1PDBqW3qaszwxusQhgYG++7Zs2keH4zIWJ4hrJr17/h8OFbkU41pMv6ICEQQqGw2q4C4c2yRzHkOGlc+6x0DOKCJvNuf/JsL06e7R1nS4VSRXti77mHxXAyIRyoj+KaR5Lnrc6FPZuc2PBHttXQMOGur1fELXe5gNNOM44Z4PFPvb2mxtBjorSmqK/n9evr2Sno93NoRX39uJsqFAItHLu6WMDqGOCWFn4iqq83E1h3d/NLV30ZGTHjY/x+HiTX0sLvWgiPjrKonT2bhfLoKHt4dYlEh4M9yHY7f3Y6ORRizRref2Mji2Ofj+OOs4n3nQTPbyZEDM9A2tvvziiEgcxZHyQEQphqrLbb4fwo9vpuyWn7cxvL8Myh+ODHuWUOXLZswcQ1Uih5wmHgkUeA555LVsZY4ZKbBnDCBclLd6fi7v8ox6U/jh9J//cflx0TwsnQvd0XXWTOW7yYHXTW8NDEirarV7MO0Z5hq1gWphHaE9zayq5+HcbQ1sbGEQqxAHW5eFl/v5mXd2SEX52dLGr7+9kYOjrMgXRKscCNxUxjCQTMdGmhEB+nvh5YuJBFMhGHSQAcG2wtiJEsL3GRIGJ4mpNscNHu3VchkxCWkAeh0KSz3QjKcxbCAHBSrQdD4RheOmrGZV44359mC0HIja1bOVvEpk2cRi2Rd385mLMQBoA3n3aj6+DQsawSezY5sekvnrh1iFh7RKOsUZqagAsuGLuvTI41LZiLUJMI2aJjddraWAhHo8D27RwO0dtremx1/K7DwV7h1laeT8Sf+/vNkAePh4WuzgPscJg1xHU8sMPBoRA6zZrfz90Pbje/V1SwcdXXJ68MVwCvbzaIGJ7GJBsYt337pwGkT8cjI+eFQpPOdodtS/Fa+Ya89mu3Ed5e68H+gRBcNsKF8/2okcIYwgShC2o89xyXWQ4nXGrffvEI1n0m9wFyA51cH/nJ//HhPf8exM5/uvD3H5chGqZjGkWHa0YiPB6pvt4sAqZjhnOhSDWJkIpEj2owyGL2pZd4cFxnJwvjoSH24irFxuJ2czeA18vCd3CQvcThMK+rvbk2G2+nhbIWxTpG2OnkUAm3m8MndL4+HSLhcpkhEWVl0y7uRu4SBSLXVGfJSJYLOL0QJqxc+QcRwULeTITdAqltVwFphfDx1W4cCUZQ5rBhUYUTL7YPYySq4LQBZ8/hAUWVbjs+s6Iq5zYJpUcuPbZbt3LWiHvuic/+pKlbHME4UMLSAAAgAElEQVRHfziYcvunb/PipPeNYsvfPJizLILlZ4bgcAJ97Tbc+RWOA37tMQ9ee8z0BjscrC0WLmTtojNW1dRwnG9dHTvhvBL+PrNJVi7Z6QQee4y7KQ4cYGGrFIvTaNTM8UvE8cR2u5mAeniYDUoLXaV4fcAUxoODpjAOhVjglpVxCEVjI28zMsKeYB02oVOS1NVNuyetjGKYiH4D4L0AjiqlVhvzqgHcC2ABgAMAPqqUGv9IgRIhn1Rnyci17HFDwxdFCAt5M1F2y9uOtV0F4KVAEpVh8OXV1fA7bXHzTpntBREhphRsRDm1QSht9u4FduwA3nyTxe2CBcD735+88ERLC/Db3wJ/+lNyIeyrjOGrf+4duwDA3s1O/PqLFVCK8NStZZYlHMpGBChl2q7NxvMcDha5c+aw4PX7WXdUVLATLhxmTbJgQXyRDWGGYU1dosse60ptr7/OXuGBARakOgWaFsOJaMNK7NKwopQpqvU11enkY3g8/OSojW901KwMN3u2mc5Ep0ibRmTjGb4TwC8A/N4y7xoATyulbiKia4zpb05882Ymqaq7bd9+BbZvvxx2e7XRS9Gd1PvW3n53VnHBVuz2Gixb9suJ+gpCCZLKbnfvvuqYtziT7XKmiNuQaLsR+LElsD/pcY8b/jTe946/J11GxsVahLCQC319XDr5wQe5Gu3gIDvO/vIX4GtfY1Gs19u0CfjJT4ANG8ZWigWAFWeN4oqbkywA8IOzqzEyYEu6DGCbVZZTwetlLeN28+faWha/Ph9w/PEsfGMx9mY7naw7EmsSCDME3W2hK6rs3MnZIgAWoBs2cFhEMMjCNxQyPb2pUCq9ENbEYqYQ1k9n4TCfAHPnmh7gQIDjgqurze6K5cvz+rqFJqMYVko9R0QLEmZ/AMA64/PvAKyHiOGsSe3R5Se5aLTLsm689629/W7s2PEZKJVqgIYTRApKRY7NIXJh2bKfT0TThRImld1GIl2IRNhm09kuC+H/SbqPVEIYAE5Z/PF8mywIcWh98dBDwC23sHfYyvr1XJ9g61bghBPYI3zHHanLK9sdKqUQfvwXvjRCOB6dFcLrZcddIMDaQxfvmjOHdcY738l6KBQy07VOUDVaoVjQRTJ0OrSuLu7C2LePl3k8LFb372ehHAqxhzaTEM4VpeJDK1wuDk73+dgY3W42woULzfjgaRYnbCXfmOE6pdQRAFBKHSGi2alWJKIrAVwJAPOl8DmA1NXdUmEtkLFv37VphLAdDQ2fw+HDd8TNVSqPCgWC2G4CudotEG+77BEey8Y0oRFNw98B8M6cjlnqiN0mZ+9eHm+0eTNwww3xIZhWjh4FfvAD9soODJiVZxOx2RWu39SVfCGA9b/JHMirq9XOns2ZIRobWWv09rIQj8VYX9TUmGlfTz89c6xzkWavykjJ2q4ulbxlC4tfPfgN4Kejhx5io3C7zYFvAP/J2XiE80EPjHO7+XN5uTlS02bjNldWmgJ4mj+VTfoAOqXUbQBuA4C1a9eWpCpLHHRUU3MR2tp+l2QAUWq0CEkfJxxDV9cjGDuILpy22pyQHLHdeNt1OKoBOJEpW0kipoCOj2HrcZyPnWX3pN22PnQ79u17VGw3B8Rux9LXx4PuN28Gbr/d1BKpiMVYFKfi8p/2Y9W6TOnTxobu2GzsYPP5WGzHYqw33vY24OSTWXPU1QHbtrH2sdvZYwyw7tFhGukyQSQba5Usw1UxUpK2u3cvG+f69SyI7XYWuKEQG0tHBz8Z6UovOiRCkyw2eDzowhleLxukDoGorTWTVPv9bKiNjfw5MZn1NCRfMdxORHMMr/AcAGkuG6VLe/vd2LXrqjFdx21tv0NFxeno7V2PRIGQGi53mM47x8uSi+VcB9sJpU0y241EukDkAlAGpTKoiTh0uWMbgBgUgAOeG9Hu/lzqLVQvlg1dAUJUbFcYN5s2AU8/Ddx55/icaE6PwnUbUnuDAeDgGw789t8rxsx3ucz438pK1hHa+blkCbB2Lfd8B4OsP7S2sBmRFj5f5hRq1rFWGl1jYZprlZlJXx/w7LPsEd6xg13/waCZHk2/RyKZ9zUR2O0sgp1OM0B99mxOo1ZZye9z55rr61LOM8C48hXDDwK4AsBNxvvfJqxFM4TEkfdWYrEgenufznGPLJprai5KGXcZjQ7Cbq+OEzCaTNXmBEGTznY5RCfeIzZiW4CjzstRGXkaFdFkadGiaG+/GwBhwH4StvkfS3v8k/uaYId5bLFdIRPpwgL6+jgG+A9/GCuEl70jhAUnhrHxPg/6j9qRGoUPfXsQp3x4NOUah3fY8X8+kTyln84AoQfjV1ZylqqaGrMCHBFrkHCYBfC8eez0mzWLv1NdHeuUI0dShz8ELaesTjzg8fD8GaBXZg4vvgg0N3OBjEOHuFjG4cP8R42M8B+vcwBPBQ4Hv9xuFrwVFWyUTicb4qxZZv5gK9qgZwDZpFb7I3iwXC0RtQL4HlgE30dEnwXQAuAjk9nI6ciuXVflFAaRDe3tdxthEMkxPXfxXdlSbU7Ilvb2u7F9+ycBZOc+C1E9tpZvBgAcxldQGX4Sc0b/B+XRl2CziObn9z+HPYG2tPtaOfRxlEVeiRPCYrvFSzIBOpGxqsn21dLCRbS057Stjee5XKwrDh7k+/iSJawpvF52tt16a/ICGTov8DmfGcbDP/Vh3xYXDu+wwwxxUPjY9YNYc1FqEQwAt1wWwKHtyW+ntbVmqKffz23SBbuGhjgjxJw53F6bjUMhurtZHOuMEosWsS6ypnVLFv6gdUlra3zmi0CAjyEUAd/5jukF7urikIdIhA1+aMiMAZ7MsT6cz4/fddyOUvzEVV3NBkrERnPeeRwGYbezgNeGVV4+o+p4Z5NN4pIUi941wW2Z9pjxlbkNMsqW3buvQiTSnXYdpUJwOGpgt/vHXRhBKB2ShUVkosvxfuwu+3XcvF7n+eh1ng8AWNu3EDaM4KDn2zji/lLafa0Y+ggCkfWG7TaJ7RY5yeJSgeSxqnpsEGCOtckkcjdt4oHytbW83OVi59n27TxwfnCQxeXs2awj3niDHWx6cD1g5ukdHGTNYeWbj3Sjsj7+ge/i/z8IGA9i3zqxFv7qGK59Kv31FgCuf1c1hnqSZ43Q4jQc5nYOD/PvMns2O9VWrmQR/MwzHDYB8PcIBnm5/l1ravg7dHbyfL8/efhDIMCaxSqEy8tZSEuoxBRjfZoD+PNdd3FKtO5uFr7hMP+RumLcaPqHrgnD6WTB7XKZVeScTh7FWVdnVqVbtIhPWn0yL1wYfzLPIIOSCnQTRLqu5YkiEumCw1FzLI1V6vW68c53dk5aO4SZRT62+1bZ/eh3nJ12nXTp0qyc2lcPMsKAxHYLj1WYJhvQn6wGQFsbC7TBwXjRtXUrZ4nq7ub7bmsri7WmJvbglpfz9n19wO7dXO64o4NFcG0t348bG83iGNYqs04nvzo7s0udCgAOl8IPN2Z+4Lvxlcw22HHAjp9+OHWlQ5uN9cbgIAtz7fW127kn+oQTeJBeby/rpEiE9dG2bfw9fT7uOV+8mEW9NWzUZmOB7PeP1SN1dfx76hAJnYItMVRiumacKEoSf0zr0+LOnfxHxmI8SE7/4YOD/DkUmrpwCO0J9nr5vbbWNE6Ph0/4k0822zRrFr/0hWAG1/AWMTxBJC8vO/EoxV3H6Y4lMZZCLuRqu+lSoeXCvOHrMCt83zEhDIjtFppnnuH7tqahATj33Ph1gkEWv6+9xvfzKkMPdnSYMa/Dw3yvraoyq7Zu3gz09LBeGB7m+/Ls2bysp4dF+MCAKWztdl53dDR1erNcyFYIZ+K1x13Y8bwLbzzpTrteLMaaQn9/nUnCZjOzRdTUsBbx+VjstrXxQwERi9jubp43e7aZVaK93dRSHg9vbw2X8PlMATwywu+JhTmmc8aJoiPxx7TbWRy3tPCf+frr/EdqQ+7sND/rp7upwGZjL7BOXu1wcJhDVZWZvaK+ng1FG0tjY8mUNxQxPEFM1Yj3aLQLK1felTYco6bmoilpizAzyMV2252Xjft4c0d+hHmhXybNSCG2WzhaWuKFMMDTLS3xHuJ//AN47DH28irF982qKtOj29bGHk6ro6yigtfv6uL5OiRSv7QAtg5wS8wgNV4mQgj/8JxqBPuyK6QBxH+fWMzUPiMj/DpyhGOH58xhXRKJ8HpeL3//SMQsQrZoEQvh7m7+vaqrk4dLBAI8vWePmZ1ryZL4uO7e3vgBdnr+DHX6TR6J6TsGB4FXXgFefZVF78GD5klls7EI1gUypiJDhK4iR2TW8g4EzJzBCxbwPGthDX3ilpeXVHlDEcPjRMcJ51IaeXywcZ9++gG8+OKCpII43SA7QQDi8wdzyjP2zioQYvCh1/Eu+KOvYNi+BJ7oXtgwiiH78djv+1nS/a0c/BCc6ij2+H6FoH11yuN+cNY/sWLuj/Dii/dhdHSsGBbbLRzdKcJju7tNMfz88xyf29nJOsBh3EGiUdYEQ0Ps5dW9v263KZq1AJssiBQq58TQuCqCA6860bgygv0vO1HVEEXTmtRxFNetq8aKM0PHBtOl4rvvqEF4ZPxlv0dHWQeFQvx7ud3mmKmyMn5pZ6HbzdN2O4vl1lYWwjpEpLWV51tDIPr6xpaNHhgwxW4wyNu1t5tiua6OewFEDGeBNQhe09YG7NrFf+5LL3FcTzjMcTBDQ/yHulw8bzIKZCSiK8fZ7SzC9XQkwp8bGvjpqrHRzB9cX88hHYCZP3iaF9LIBRHDSUgskpFqEM9UxAmPRR0roCE5hYVEsrHdsXYbRa9jHXaU/Tnn41WHHsCy4c8fmz5h8BwAwLBtEfZ4b4UiO1YO/SscqgcEoGekCZj7AbHdIqS6Ov38vj52dOkYWKfT7Pp3OPgeOzrKond0lO//ukDWyEj2cb258pHrBnDie3MfeHTrpwNofo09Yq8+7MGrD3sAKKw4K4SPXT+ILQ+48cjNZVAxIFkBjfEQjcZrokiEvb/RKL+UMr3n8+cDJ53EeisY5OVeo7jdwAD/H1bnXVsbz7f2dg8M8Hxd5nnPHtPD7HTy8re/fUK/4sxk61b2+obD/OPqmJfDh/npor+ff2g9ylN3gwBTMzhOC2CAxawW4U4nP1kpxYPg1qzh91jMFL4AsHw5x+M4nSUXTC5iOIFEoTA62oydO68EANTVXZrSozYWQu7eYi5KkAktGFIV4JC4y9Ikne0CSGm3YarOSwjPH/4uGkLJc157Y/tw/NAFY+aL7RYv8+ezwygxZlh7hYNBswqaFmrRqDmYq6PDDI/QuXJ1zO9kOcPO++JQXkL42lNqEIskE7iEHc+58YOz0scDTxQ2m6lX9IC7QIDDSZ1O/l3XrAGWLWMdpsdc9fezgK6u5ljfXDSLDlu19u7HYhMTlz2j2bqV05w0N7OBu938Q27ebJ4YAwNs8Dbb1A6MA+IHx9XUsAEND/NJWFZmVn055xweven3cxfByIgphisrk4+aLQFKSgxn4zVLNpgoFgsaoRAY41FLTW5CeN06lbWnWQuGRYtuGLO+5GWdmYzHdnftugpKDSe122HbYrxWvjGvNmkhvHLlXUnsNvnDoNhucXPuuamzSYTDHF9aV8f3z1CINcCsWcCKFSzQOjo4TCIWM7M1OZ3mQK6J5APfGsRpH8l9x4/c7EshhKcOm80Uwg4H/65KcY91ZSVrKIeDnXcnnsjC1ePh39jlMh2PPp+Zkk1TX8/hnonp1XRaO+01ttlMz7DHMza0oqRJzA7R12cWyOju5ulDh3heT49ZJS4S4R91qgbFaa+vTkpdVcVPsHV13A6Xi0/GWIwD05uaTCEMcIxNiXqCEykZMZzJ46tJ13072RkjdDu06HE4qhGJ9CNVAY3E9SUv68xkvLabKnewgi0/IayiOK2//thkMjusqbkIbW2/Syl2xXaLl0DAvDdacTpZVB13HAurzk6+165bxx7htja+H9tsZq5c7ZQKh83QyYnguHNH8xLC937bj62PeCamEXlit7MWCYX4Ny0r499Nj28qK+MHEY+HtY0e4GZ9oHC7+eXxjPXoBgLA6tWm009XuNM6p7zc/G/1vrMp9VwyJEu14fOZGSLa23kkaHc3rzcwwCJYx7ZMBToGuLqa2xcK8dPTggVm0PmJJ/IyfSKuXs1PWVoI6+9Wop7gREpGDKfz+FpvwOm6b7OLZ6SUJZGzoa7u0rj2ZPIIJq4vzDzGa7uJxOBAmGbh1YrXU67ji76OqvBj8EdfRYSq4Ituh0sdgUP1xqVC0ySzw0DgDLHdaUa6lFs+H4uqwUF2JukctkuWcAap6mpex+vl9To7eXlVFbBlC48v0sW28sXli2Hh2yO47L9SuzHfeMqFVx92wxdQGOoldB+0o+eIfUIGv2WL1iq6yJfNZoaUaIEbibBAnTWLPcLV1WZVXC1Sm5o4RGLPHp6urjbjrxsbuTc8GYsX8z6T5RGur+f/LHEAXX198n2VFNZUG11d/ARXVsYi98EHgQMH+KlPnySh0NQNigNMA5k1i42jqoqPPzjIf2RNDRvZ/PkcX7NkCZ+QVs+vJJhOSsmI4WwH7CxadAN27PgMlAolrNcMwI70oREAoLBs2c+xfXsuKajsKZeIYBDGa7s6Fn3EthBbyzelPE6VYwAre1bn2PshtjtTSMwSBcSn7QoEzIpo1hDDQABYupQFb0cH34dHRoDjjwfOOotF34IFwP33mzlyIxEz01Q26dPO+MQw3vv1sdlHNDe+pwr9R1Pb4kTjcLD+0albicxpr9cUl83NphjW4ZurVpkx18cdx6JVD6hbtoz339cHzJsHnHkmT1dW8nrao1tdzbrHGv6QSKr6CNpzXFmZ3HNc0uhUG3v2mK71I0fMnIDDw2bJ5GT5ACcLIn7C0t0Hxx/PL52jb3iYPdRK8SC4piY2kuXLx+5rBhfOGA8lI4ZzGbCjUvblZQ6Gd7ubUFd3qVE6OTvvcEPDlZlXEkqWXGw3hCps8z+AEfsSAIA91oOoLXWVLCtfOH4h2ttvw/btVyAbWwfEdmcSwRTPQNa0Xbq8cqJjKRAAzj+fM0rplGtEZq2Bri4WxKOjZshEood42TtC+OTP+mE3Up52HbShZl52QmM8QpiINYTdrosamaLT7TZDMh0Odr7p24PPx7rkhBNYTGrv7UknmXG7IyPAc89xhi0dE7x4sVkN19pjvXo1xwgnc9ppT6/Lxb+p9h7nK2LTeY5LmnDYTOY8MsKe4OZms0qMFsTakCcbt9s0Pr+f//DGRhbCZWUsegFuo+5eWLaMn5RWrZr89s0gSkYMZztghwfK5Wfk1v0tXfrzpMerqDgdvb3rwWLDjoaGK7Fs2S/zOp5QGmRru7v3/RAvV7wZNy9bIfypOY8DMD25YrulR6rc+onzUzmWtMh77TXWDAcP8vvhw8DGjexgGxoam2tY5wf+9C/64+ZnI4Qf+ZkPz/8hv6IAZ57J3lGbzRz7VFPDKcYiEVMs6hCH9nbWJGVl/B10FquFC9kBd8EFPF1XFy8w3/Y21ip68KHTyfuKRs3CF3V13KsNpBamgQBw+ukT18stDsIE+vrMfHM69KCjw3TbDw6yCNbTujtgotAjTnWeQo/HTIfm9bLwXbmSyxHW1fE21q4CgOeXlYmrPw9KRgxnO2An3zyndnsNli37+bH9yQAhYaJItKWY53QEa36KV0ZXoXt3L6rddrzWNQp4Xsh5377o63hPxf2orzdFrdhuaaLDIBJjhrO9p+7dyz3LfX1chOvAAXZmbdjAYjASAZaeHsLKs0JwehVq50cx1G3DcefmV2bunmvK8cYTuadAq6gAPvxh4Jpr2IOrNZDDwWJYi0wdP60F69lns7fXOq+uLrU3VzN//tgxSnPm5C9qRcROAIk//tat/ISi5ytlFqgA+HM0apYQ1OlAiMafPk27+XU3hNfLJ87s2Xzc0VFefs45ZuaHRYvY8Pbv5zbNm8f7GhlhwSyD4nKmZMQwYMYw6kFp27dfjn37ro270WczCMlur4HD4c8oFCRmUpgotC1t2P8Mnus9ARgEMMj5VQ8O5jci6ayRk7F40fWoqxvr3RXbLU1ShUFkQscbd3UBTzzB4RIdHTzWaGQE8PhjuPjfg3llgEjk1YfduO87qVMfuFz8brfz+KI5c8wsU4sWAWecAVxxRXyIRzLtkOq3SBUmkisiagtE4ijRw4fN1GnBIKdKGxw0U6aFQix83W7u2gDMpNCU56BMm81893j4qdPrNaupLFzI3l2vl5/AdNC4tTLc/Pls2NbvMneuCOE8mZFiOF0GhkxpqpJ1SVux2XxxHmBBmCjS2W1UKfzi9cMYjp0wrmN8Y03NsVpaRPvH2WJhJpKPSNPjjh5+GHj6abP+AADUL43gqnt70+8gA8/+xosnflEGzl2dXIAsXAh86UusWRob2eu7YIHp8MtnsFiy30JE7DQmcZTo4CB3W0SjbMQ6Vtjt5qcpPWgtFOLtrHl7ATPYPJ132G43A9O1eLbZzCB0LXjLy1no6pKOfj8HkpeXp84HnO/TqzCGGSeGM4ndTGmqEruI7fZqEAGRSLd0FwuTRqLdDo8exvadX0bz8Gwsm3Mu/tkWxHAs+y5hT3Qv5o/8EJWRJ+F0L8aihd9BQ93HQfl6MgTBoK+PPb4AC05d4vdPf2KvcF+/gr82huNOjuDAK86chfDWR9x49jde9LXbEB4h2BxAZPTYI1zSbVatAn75S9YMOhWcZjwhCcIMI3GU6MgIi8+DB7miycAAC+H2dhav1dVmJgmAhauuLKdDKTSJglhXhPP5WNjqUoy6Eo1OhaZzFNbXc1dGUxMfv6mJwx+snuBkyNPZhDDjxHAmsZtNmirpIhamGqvdNnu+jyPuL/GCHuCZnp6s9vHeJj9WV+uCArUAHpr4hgolzd69wJtvsmYIBoGdO83iD489ofDp23sxe2HuMZQ3nFeNwW5b0mWxDLu7+mrgX/6FBXG6wWeiF4Qxo0Gtpfd6ekzROzhojvTUeQC1I0GLWR0vPDrK6+h8eXognM/HYjoWY9EbCPD6Xi+v7/fzk1pNDa/T1GS2b948HskpleGmjBknhjOJ3VzSVAnCVNEXtqPb9SUcdX0CI/ZlOW3rUu34/PErUO6cujyrwswhVVxsove3r49DIQ4cYEH81FNAcFhh8doIGtaM4ptP5R4PvPmvbjxwoz+v8sh+P3ui04lgoURJ1RWQbJRoWZmZnaG5mfPghULmSyeP1sRiLGp9Pha+ugKdNbNEZSXvc+5cbkdVFQ9sW7mSq9jpOOGyMlMoJ8bySOzvlDLjxHAmsZttmipBmEyUUugNxbC1cwRbOoYRLX8p622rwg+jafi78KgW2Gw+LF9+G8qdx01ia4WZSrKKcwMDHPfb1mY6tc48k4tZbdwI/ON5hQM9EZx51TBWnZ1bJoinfuXFs7/25SV+NXY78I53cFjE6tV570aYqSSmAbHmrQPi42z7+/mpanCQxa2uPKfrZEejHAOkFAvUUIiXR6Mc16srx9hs5jZOJ5dCbmzk/ROxB9jnY6G7bBmfaNbKNRL7W3BmnBjOJHYlbZRQaFoGwnikZQC9odxyVM73O3Fu+UPYv/97GFUH4XY3ie0KeZOs4txLLwG/+Q2wfTvXFnC5+L782mvAGe9U6K0exmn/GcRZ3uT7TMW91/qx9VFP5hXTUFPDOXvf/36uOSBCWBiDNurWVjP8oaOD3xNz4AUC/HnPHt6ms5OFbFUVr+fxmGEQugJcbS2LV51rWFdBUYpfc+ZwiMPpp3OXSijEnuZwmI81MJC6uorE8hSUGSeGsxG7EhMsTDbtwQiGIzE0lTuPDVpTSuHF9mE8fySIZDUO53mOwjPwa/Sq+fDYwjhnXgMa6j+B0WgMdiI4bATgUtTXi+0K40eHR+7dy3rB5wN+drNCtDKMsNuGnsN8e+jsBCK2GOZ/aAA1y8cWJOrvILz1rBsdzXbMXRXBzhdceO1xHuzpC8QQ7COkGviWiMfDeqC21uzRnjuXC1o0NHBvdXW19CALSejr47y7bW2mENa8+iov115gl8uMr7Hbef1QiMXwrFksgPv7zVhhpTitWkUF5+fr6GBjrKzk1Gx6sJ3fz2L47LN5X4cPsyjWXmpdeUWEb9Ex48QwIGJXKCz7+0O4dy9X0zq9zosTajxw2QgPtwxgX78pJmwA5vqdWFHpwupqD1z2WgA/GbM/tz35wCJBGA8+H/DII8ALL7BjrK8PWPvZAaw+L4TwKHDX1RU4ssuBqoYoPnLTACrrzZ6MoR7Cnk1OvPygB3s2OqFUcrEb7MvOduvqgMsvBy66yNQMDQ1mvLIgpEWHRrS1cQENpTivHmA+9Y2M8Dp69OfhwxyeUFfHxu/zsUgeGOBsDk4nG2FNDa9/9CgvD4d5G53toauLxfHgILB0Kdfjnj+f96nx+82wiFSlHoWCMiPFsCAUgp7RKDa2B7kanMGL7cN4sX14zLpzyxz4wIJylLtk0JtQGA4eBO67DzhyRGH+iWGcfWUQC0/kVFFON8aUR9as/60XT/7Sh1g0/7hfh4OdbE1NwCmnAF/+soQ9CHmSLDTi0CH26DY1mdkfIhFT6AaD7AkeHuZ5Wqza7SxWHQ5e3tjIYrijg/cRi7FHWHt2a2tZZA8OskHrgXjA+Es6ClOKiGFBGCftwQg2tgexozeUNPwhkdNme3FWgw82yfkrFJD771fwLw7h0muDmLM8czq0YB/hz98tx47nXXkdz+XikIeFC9mBdvrprFWS5QYWhKwJBlmMaiHc1GQuq6pikdvbywI3GDQ9xbpUYTDIhS2iUTbGwUE2SK+X5w0O8jpeb7zYnT3bzCu4fLnp+dXdLIGADIybRogYFoRx8tLRYWzvTT6q3mkzcrMrwGMnvLepHEsC+YkJQZhIduwGzv/qIHwB8xEuGgbsTv483E9w+xVsNsYMcp0AAAdTSURBVODgGw7cc005eo/k1pNRUcEaZM4c4CMf4djfVat4megDYULw+dg7q729LhcL4qoq9uwuXMiB762tvFxvo8MVdByvz5e69nYoxB5lja4WF4mwdziRYFAGxk0zRAwLwjg5rc6Lt3o4NGJhuROn1Xkx3+88tjwG9h5Xu+3wOCT+VygO3A7Cxnu9OPfKIEIjwJa/evD8XV5D8HLZY18ghurGKA7tcACK4Pdzz3Jisa3KSg53iMWA3btZBJ97Lvcsl5ezF/iUU8amfBWEcRMIjBWrs2ZxTt+FC+NDGkIhHmSnhbAWtdYME4n71lkntm41A9q1F7i62sxWYUXigqcdIoYFYZzM9jqwrsGHBeUu1PvGnlJ2AA1lzrEbCkIBWbgQeOhWD4gUXrzPi4Eu64Mah/AE+2zHBsGVlQEf/CA72Xbs4MH1TiePFbr4YuCSS1hvBIM8xmjYCJWXQXDCpKC9tuEwD3QbGOA0Z7oEst0+9unr/PNZ1La3m6I2mzjeQIBDKBLjf+fP5+NLXPC0R8SwIEwAp9WJJ0CYXixcCFT5bdj8pzIgwmJ3eDi+kJZG1wq44QYu0rVrF2uO6mp+WavAiQ4QJh1rtZjOTvbYLl8+NoVZMtasyS+ON1X8r8QFzwhEDAuCIJQgxx3HRSyam1k/EJkhEF1dnGrV4eB7+wknAN/4BjvC5s/nabn3CwUhsVqMx2OmNss2hVm+cbyptpO44GnPuMQwEb0HwM/BPcF3KKVumpBWCYIgCJPK0qXca7xtG/cwl5ez+HU4gJ4eFsY+H8f7nndefKELufcLBSMYjJ/2+9l4R0biSxyLgQo5kLcYJiI7gFsAnA+gFcBmInpQKfXWRDVOEARBmBx0COW8eWYmqBUrOA64uZkzSS1dKppCKDKSeXznzuVBc06ndFcIeTEez/ApAPYopfYBABH9CcAHAIgYFgRBmAYsXmwOerNqCCl3LBQtqYpZiNEK42A8YrgRwEHLdCuAU8fXHEEQBGEqkZAHYdohg9aECWY8SU+Tlc8aU4CLiK4koi1EtKUjWT4+QShSxHaF6YjYrTBdycl2AwGu5iJCWJgAxiOGWwHMs0zPBXA4cSWl1G1KqbVKqbWzZs0ax+EEYWoR2xWmI2K3wnRFbFcoFOMRw5sBLCWihUTkAvBxAA9OTLMEQRAEQRAEYfIhpcZENmS/MdFFAG4Gp1b7jVLqhgzrdwBozvuA46MWQGeBjp0KaVN2WNvUpJSacpdBAW232P+PYqIY21VQ25Vr7hikTdkjtltcSJuyIy+7HZcYnk4Q0Ral1NpCt8OKtCk7irFNU0UxfvdibBNQnO0qxjZNFcX43aVN2VOs7ZoKivG7S5uyI982jSdMQhAEQRAEQRCmNSKGBUEQBEEQhJKllMTwbYVuQBKkTdlRjG2aKorxuxdjm4DibFcxtmmqKMbvLm3KnmJt11RQjN9d2pQdebWpZGKGBUEQBEEQBCGRUvIMC4IgCIIgCEIcIoYFQRAEQRCEkqVkxDAR/ZiIdhDR60T0VyKqLGBb3kNEO4loDxFdU6h2WCGieUT0LBFtJ6JtRHRVodsEAERkJ6JXieihQrelUIjtpm1PUdotILYLiO1maI/YbpEidpuemWi7JSOGATwJYLVS6gQAuwB8qxCNICI7gFsAXAhgFYBLiGhVIdqSQATA1UqplQBOA/ClImnXVQC2F7oRBUZsNzXFareA2C4gtpsOsd3iRew2PTPOdktGDCulnlBKRYzJjQDmFqgppwDYo5Tap5QKAfgTgA8UqC3HUEodUUq9YnweABtTYyHbRERzAVwM4I5CtqPQiO2mphjtFhDb1YjtpkZst3gRu03PTLTdkhHDCXwGwKMFOnYjgIOW6VYUgRFZIaIFAN4O4KXCtgQ3A/gGgFiB21FMiO2moIjsFhDbTYbYbgrEdosasds0zBTbdUx8WwoHET0FoD7JomuVUn8z1rkW7OK/eyrbZoGSzCua/HZE5AfwFwBfVUr1F7Ad7wVwVCn1MhGtK1Q7pgqx3fFRLHZrtEVslxHbzQKx3cIgdjt+ZpLtzigxrJQ6L91yIroCwHsBvEsVLsFyK4B5lum5AA4XqC1xEJETbNh3K6X+b4GbcwaA9xPRRQA8ACqI6C6l1GUFbtekILabP0Vmt4DYbhxiu6kR2y0cYrfjY6bZbskU3SCi9wD4KYCzlVIdBWyHAxyQ/y4AhwBsBvAJpdS2QrXJaBcB+B2AbqXUVwvZlkSMp7yvK6XeW+i2FAKx3bRtKlq7BcR2xXbTtklst0gRu83Yrhlnu6UUM/wLAOUAniSirUR0ayEaYQTlfxnA4+Cg8/sKbdgGZwC4HMC5xu+z1XjCEgqP2G5qxG6LG7Hd1IjtFi9it+mZcbZbMp5hQRAEQRAEQUiklDzDgiAIgiAIghCHiGFBEARBEAShZBExLAiCIAiCIJQsIoYFQRAEQRCEkkXEsCAIgiAIglCyiBgWBEEQBEEQShYRw4IgCIIgCELJ8v8AlRWHG/C0ZTgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41d98e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41a12400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ae2ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50 500 - 1.2550585496502118 0.06949886604581272 [0.06235377 0.27086723 0.25082877 0.25716045 0.32282513]  -  1.0000557883913375 0.7409118933659246\n",
      "200\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac465d6208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41e395c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41b83630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 200 - 1.111402718718909 0.037815841871729546 [0.06639261 0.16022705 0.13711363 0.13798378 0.22134213]  -  1.0185051208314926 0.6390442069123938\n",
      "20\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41a25518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac4228be80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41e700b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 20 - 1.0978736963234133 0.051478362792862414 [0.04844937 0.05515969 0.05134457 0.06311297 0.09440312]  -  1.0277268888287128 0.44626210003965255\n",
      "2\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41aa8c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac421f7710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41b839b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000 2 - 0.9975959693099741 0.01263461369258264 [0.03698151 0.04099889 0.03985639 0.03981471 0.08708167]  -  1.0109327053799495 0.3970512321755208\n"
     ]
    }
   ],
   "source": [
    "results = []\n",
    "for N, nb_epoch in zip(Ns, nb_epochs):\n",
    "    rep_results = []\n",
    "    print(nb_epoch)\n",
    "    for i in range(nb_reps):\n",
    "        X, Y = gen_data(N + nb_val_size)\n",
    "        X_train, Y_train = X[:N], Y[:N]\n",
    "        X_val, Y_val = X[N:], Y[N:]\n",
    "        model = fit_model(nb_epoch, X_train, Y_train)\n",
    "        model.eval()\n",
    "        MC_samples = [model(Variable(torch.FloatTensor(X_val)).cuda(gpu_id)) for _ in range(K_test)]\n",
    "        means = torch.stack([tup[0] for tup in MC_samples]).view(K_test, X_val.shape[0]).cpu().data.numpy()\n",
    "        logvar = torch.stack([tup[1] for tup in MC_samples]).view(K_test, X_val.shape[0]).cpu().data.numpy()\n",
    "        pppp, rmse = test(Y_val, K_test, means, logvar)\n",
    "        epistemic_uncertainty = np.var(means, 0).mean(0)\n",
    "        logvar = np.mean(logvar, 0)\n",
    "        aleatoric_uncertainty = np.exp(logvar).mean(0)\n",
    "        ps = np.array([module.p.cpu().data.numpy()[0] for module in model.modules() if hasattr(module, 'p')])\n",
    "        plot(X_train, Y_train, X_val, Y_val, means)\n",
    "        rep_results += [(rmse, ps, aleatoric_uncertainty, epistemic_uncertainty)]\n",
    "    test_mean = np.mean([r[0] for r in rep_results])\n",
    "    test_std_err = np.std([r[0] for r in rep_results]) / np.sqrt(nb_reps)\n",
    "    ps = np.mean([r[1] for r in rep_results], 0)\n",
    "    aleatoric_uncertainty = np.mean([r[2] for r in rep_results])\n",
    "    epistemic_uncertainty = np.mean([r[3] for r in rep_results])\n",
    "    print(N, nb_epoch, '-', test_mean, test_std_err, ps, ' - ', aleatoric_uncertainty**0.5, epistemic_uncertainty**0.5)\n",
    "    sys.stdout.flush()\n",
    "    results += [rep_results]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('concrete-dropout.pkl', 'wb') as f:\n",
    "    pickle.dump(results, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.99725588 1.67696622 1.25505855 1.11140272 1.0978737  0.99759597]\n",
      "[[0.06126967 0.39897382 0.39423513 0.39553675 0.40388337]\n",
      " [0.06281737 0.3798245  0.36434355 0.3677373  0.40271112]\n",
      " [0.06235377 0.27086723 0.25082877 0.25716045 0.32282513]\n",
      " [0.06639261 0.16022705 0.13711363 0.13798378 0.22134213]\n",
      " [0.04844937 0.05515969 0.05134457 0.06311297 0.09440312]\n",
      " [0.03698151 0.04099889 0.03985639 0.03981471 0.08708167]]\n"
     ]
    }
   ],
   "source": [
    "best_tests = np.array([[r[0] for r in result] for result in results]).T\n",
    "best_ps = np.array([[r[1] for r in result] for result in results])\n",
    "best_aleatoric_uncertainty = np.array([[r[2] for r in result] for result in results]).T.squeeze()\n",
    "best_epistemic_uncertainty = np.array([[r[3] for r in result] for result in results]).T.squeeze()\n",
    "print(best_tests.mean(0))\n",
    "print(best_ps.mean(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac465d66a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ee83c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41d25b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pylab\n",
    "%matplotlib inline\n",
    "\n",
    "pylab.figure(figsize=(3, 3))\n",
    "pylab.plot(Ns, np.mean(best_epistemic_uncertainty, 0)**0.5, '-*')\n",
    "pylab.xlabel('Number of data points (N)')\n",
    "pylab.ylabel('Epistemic uncertainty (std)')\n",
    "pylab.xscale('log')\n",
    "# pylab.savefig('epistemic.pdf', bbox_inches='tight')\n",
    "pylab.show()\n",
    "\n",
    "pylab.figure(figsize=(3, 3))\n",
    "pylab.plot(Ns, np.mean(best_aleatoric_uncertainty, 0)**0.5, '-*')\n",
    "pylab.xlabel('Number of data points (N)')\n",
    "pylab.ylabel('Aleatoric uncertainty (std)')\n",
    "pylab.ylim([0, 2])\n",
    "pylab.xscale('log')\n",
    "# pylab.savefig('aleatoric.pdf', bbox_inches='tight')\n",
    "pylab.show()\n",
    "\n",
    "pylab.figure(figsize=(3, 3))\n",
    "predictive = np.mean(best_epistemic_uncertainty, 0) + np.mean(best_aleatoric_uncertainty, 0)\n",
    "pylab.plot(Ns, predictive**0.5, '-*')\n",
    "pylab.xlabel('Number of data points (N)')\n",
    "pylab.ylabel('Predictive uncertainty (std)')\n",
    "pylab.ylim([0, 2])\n",
    "pylab.xscale('log')\n",
    "# pylab.savefig('predictive.pdf', bbox_inches='tight')\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fac41ca0198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pylab.figure(figsize=(3, 1.5))\n",
    "ps = best_ps.mean(1)\n",
    "ps_std = best_ps.std(1)\n",
    "for i, (p, p_std) in enumerate(zip(ps.T, ps_std.T)):\n",
    "    if i == 4:\n",
    "        continue  # layer 4 is noise layer\n",
    "    pylab.plot(Ns, p, '-*', label='Layer #' + str(i+1))\n",
    "#     pylab.fill_between(Ns, p + p_std, p - p_std, alpha=0.25)\n",
    "pylab.legend(bbox_to_anchor=(1, 0), loc='lower left')\n",
    "pylab.xlabel('Number of data points (N)')\n",
    "pylab.ylabel('Dropout probability')\n",
    "pylab.xscale('log')\n",
    "# pylab.savefig('dropout_prob.pdf', bbox_inches='tight')\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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